tor_multiclass.ipynb

{
 "cells": [
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# TOR multi-class classification using Network Traffic Classification based on Single Flow Time Series Analysis \n",
    "\n",
    "Problem: mutliclass classification of TOR traffic\n",
    "\n",
    "Raw data from: ISCX-Tor-2016 [1]\n",
    "\n",
    "-----------------------------------------------------------------------\n",
    "[1] Arash Habibi Lashkari et al. Characterization of Tor Traffic using Time based Features. In ICISSP 2017, pages 253–262. SciTePress, 2017."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import json\n",
    "import collections\n",
    "\n",
    "import warnings\n",
    "warnings.filterwarnings('ignore')\n",
    "\n",
    "from matplotlib import pyplot as plt\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.metrics import classification_report\n",
    "from sklearn.metrics import confusion_matrix\n",
    "from sklearn.metrics import accuracy_score\n",
    "\n",
    "import seaborn as sns\n",
    "\n",
    "#Import Random Forest Model\n",
    "from sklearn.ensemble import RandomForestClassifier\n",
    "#Import scikit-learn metrics module for accuracy calculation\n",
    "from sklearn import metrics\n",
    "\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.model_selection import cross_val_score\n",
    "from sklearn.model_selection import StratifiedKFold\n",
    "from sklearn.model_selection import KFold\n",
    "from sklearn.metrics import classification_report\n",
    "from sklearn.metrics import confusion_matrix\n",
    "from sklearn.metrics import accuracy_score\n",
    "from sklearn.linear_model import LogisticRegression\n",
    "from sklearn.tree import DecisionTreeClassifier\n",
    "from sklearn.neighbors import KNeighborsClassifier\n",
    "from sklearn.discriminant_analysis import LinearDiscriminantAnalysis\n",
    "from sklearn.naive_bayes import GaussianNB\n",
    "from sklearn.naive_bayes import MultinomialNB\n",
    "from sklearn.ensemble import AdaBoostClassifier\n",
    "from sklearn.svm import SVC\n",
    "import lightgbm as lgb\n",
    "#Import scikit-learn metrics module for accuracy calculation\n",
    "from sklearn import metrics\n",
    "\n",
    "from sklearn.model_selection import train_test_split\n",
    "\n",
    "from xgboost import XGBClassifier\n",
    "\n",
    "\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.metrics import f1_score\n",
    "from sklearn.metrics import precision_score\n",
    "from sklearn.metrics import recall_score\n",
    "from collections import Counter\n",
    "from imblearn.over_sampling import RandomOverSampler, SMOTE\n",
    "from imblearn.under_sampling import RandomUnderSampler, NearMiss\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.read_csv(\"../cnsm_final_datasets/tor_multiclass.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
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       "        Unnamed: 0.1  Unnamed: 0           DST_IP          SRC_IP  PACKETS  \\\n",
       "0                  0           0  216.58.216.142.   10.152.152.11      828   \n",
       "1                  1           1   10.152.152.11.  216.58.216.142      847   \n",
       "2                  2           2   10.152.152.11.   173.194.33.97      871   \n",
       "3                  3           3   173.194.33.97.   10.152.152.11      855   \n",
       "4                  4           4   10.152.152.11.   74.125.28.189       81   \n",
       "...              ...         ...              ...             ...      ...   \n",
       "120791          1311        1311   198.52.200.39.       10.0.2.15    12430   \n",
       "120792          1312        1312   198.52.200.39.       10.0.2.15    13031   \n",
       "120793          1313        1313       10.0.2.15.   198.52.200.39    16889   \n",
       "120794          1314        1314   198.52.200.39.       10.0.2.15     1074   \n",
       "120795          1315        1315       10.0.2.15.   198.52.200.39     1368   \n",
       "\n",
       "        PACKETS_REV    BYTES  BYTES_REV    TIME_FIRST     TIME_LAST  ...  \\\n",
       "0                 0   461864          0  1.437765e+09  1.437765e+09  ...   \n",
       "1                 0    74678          0  1.437765e+09  1.437765e+09  ...   \n",
       "2                 0   108133          0  1.437765e+09  1.437765e+09  ...   \n",
       "3                 0   509135          0  1.437765e+09  1.437765e+09  ...   \n",
       "4                 0    17268          0  1.437765e+09  1.437765e+09  ...   \n",
       "...             ...      ...        ...           ...           ...  ...   \n",
       "120791            0  6689717          0  1.437768e+09  1.437768e+09  ...   \n",
       "120792            0  7268310          0  1.437768e+09  1.437769e+09  ...   \n",
       "120793            0  3854617          0  1.437768e+09  1.437769e+09  ...   \n",
       "120794            0   608083          0  1.437769e+09  1.437769e+09  ...   \n",
       "120795            0   290990          0  1.437769e+09  1.437769e+09  ...   \n",
       "\n",
       "        SPECTRAL_SKEWNESS  SPECTRAL_ROLLOFF  SPECTRAL_CENTROID  \\\n",
       "0            32615.831626          0.497969           0.572631   \n",
       "1            29684.738594          0.498565           0.592120   \n",
       "2             3140.992232          0.062492           0.473799   \n",
       "3             6003.374113          0.711139           0.510666   \n",
       "4             7820.522820          0.940996           0.581749   \n",
       "...                   ...               ...                ...   \n",
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       "120795        7826.834605          0.580813           0.540675   \n",
       "\n",
       "        SPECTRAL_SPREAD  SPECTRAL_SLOPE  SPECTRAL_CREST  SPECTRAL_FLUX  \\\n",
       "0              0.215905        0.708048       33.910269       4.108293   \n",
       "1              0.234305        0.578221       25.364824       2.249503   \n",
       "2              0.277916       -0.076864        2.225462       5.307691   \n",
       "3              0.278847        0.008315        5.167634       6.112560   \n",
       "4              0.281770        0.321528        6.800252      12.705158   \n",
       "...                 ...             ...             ...            ...   \n",
       "120791         0.320419       -0.333952       25.385595       0.206568   \n",
       "120792         0.320866        0.029524       34.689759       0.221259   \n",
       "120793         0.307234       -0.157668       26.758707       0.023137   \n",
       "120794         0.269686       -0.597276        4.102470       0.173548   \n",
       "120795         0.266813        0.049221        4.294642       0.022102   \n",
       "\n",
       "        SPECTRAL_BANDWIDTH  PERIODICITY_SCDF  LABEL  \n",
       "0                 0.543552             False  AUDIO  \n",
       "1                 0.310119             False  AUDIO  \n",
       "2                -0.129332             False  AUDIO  \n",
       "3                -0.127544             False  AUDIO  \n",
       "4                 0.137279             False  AUDIO  \n",
       "...                    ...               ...    ...  \n",
       "120791           -0.431901              True   VOIP  \n",
       "120792           -0.082447              True   VOIP  \n",
       "120793           -0.640303              True   VOIP  \n",
       "120794           -0.829831             False   VOIP  \n",
       "120795            0.200455              True   VOIP  \n",
       "\n",
       "[120796 rows x 82 columns]"
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     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "default_faetures = [\n",
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    "    \"PACKETS_REV\",\n",
    "    \"BYTES\",\n",
    "    \"BYTES_REV\",\n",
    "]\n",
    "\n",
    "statistics_features = [\n",
    "    \"MEAN\",\n",
    "    \"MEDIAN\",\n",
    "    \"STDEV\",\n",
    "    \"VAR\",\n",
    "    \"BURSTINESS\",\n",
    "    \"Q1\",\n",
    "    \"Q3\",\n",
    "    \"MIN\",\n",
    "    \"MAX\",\n",
    "    \"MIN_MINUS_MAX\",\n",
    "    \"MODE\",\n",
    "    \"COEFFICIENT_OF_VARIATION\",\n",
    "    \"AVERAGE_DISPERSION\",\n",
    "    \"PERCENT_DEVIATION\",\n",
    "    \"ROOT_MEAN_SQUARE\",\n",
    "    \"PERCENT_BELOW_MEAN\",\n",
    "    \"PERCENT_ABOVE_MEAN\",\n",
    "    \"PEARSON_SK1_SKEWNESS\",\n",
    "    \"PEARSON_SK2_SKEWNESS\",\n",
    "    \"FISHER_MI_3_SKEWNESS\",\n",
    "    \"FISHER_PEARSON_g1_SKEWNESS\",\n",
    "    \"FISHER_PEARSON_G1_SKEWNESS\",\n",
    "    \"GALTON_SKEWNESS\",\n",
    "    \"KURTOSIS\",\n",
    "    \"ENTROPY\",\n",
    "    \"SCALED_ENTROPY\",\n",
    "]\n",
    "distribution_features = [\n",
    "    \"HURST_EXPONENT\",\n",
    "    \"BENFORD_LAW_PRESENTED\",\n",
    "    \"P_BENFORD\",\n",
    "    \"NORMAL_DISTRIBUTION\",\n",
    "    \"CNT_DISTRIBUTION\",\n",
    "    \"TIME_DISTRIBUTION\",\n",
    "    \"AREA_VALUES_DISTRIBUTION\",\n",
    "]\n",
    "time_features = [\n",
    "    \"MEAN_SCALED_TIME\",\n",
    "    \"MEDIAN_SCALED_TIME\",\n",
    "    \"Q1_SCALED_TIME\",\n",
    "    \"Q3_SCALED_TIME\",\n",
    "    \"DURATION\",\n",
    "    \"MEAN_DIFFTIMES\",\n",
    "    \"MEDIAN_DIFFTIMES\",\n",
    "    \"MIN_DIFFTIMES\",\n",
    "    \"MAX_DIFFTIMES\",\n",
    "    \"MEAN_SCALED_DIFFTIMES\",\n",
    "    ]\n",
    "behavior_features = [\n",
    "    \"SIG_SPACES\",\n",
    "    \"SWITCHING_METRIC\",\n",
    "    \"DIRECTIONS\",\n",
    "    \"TRANSIENTS\",\n",
    "    \"CNT_ZEROS\",\n",
    "    \"CNT_NZ_DISTRIBUTION\",\n",
    "    \"BIGGEST_CNT_1_SEC\",\n",
    "    \"PERIODICITY\",\n",
    "    \"VAL\",\n",
    "    \"TIME\",\n",
    "]\n",
    "frequency_features = [\n",
    "    \"MIN_POWER\",\n",
    "    \"MAX_POWER\",\n",
    "    \"MIN_POWER_FREQ\",\n",
    "    \"MAX_POWER_FREQ\",\n",
    "    \"SPECTRAL_ENERGY\",\n",
    "    \"SPECTRAL_ENTROPY\",\n",
    "    \"SPECTRAL_KURTOSIS\",\n",
    "    \"SPECTRAL_SKEWNESS\",\n",
    "    \"SPECTRAL_ROLLOFF\",\n",
    "    \"SPECTRAL_CENTROID\",\n",
    "    \"SPECTRAL_SPREAD\",\n",
    "    \"SPECTRAL_SLOPE\",\n",
    "    \"SPECTRAL_CREST\",\n",
    "    \"SPECTRAL_FLUX\",\n",
    "    \"SPECTRAL_BANDWIDTH\",\n",
    "    \"PERIODICITY_SCDF\",\n",
    "]\n",
    "\n",
    "features = [\n",
    "    \"PACKETS\",\n",
    "    \"PACKETS_REV\",\n",
    "    \"BYTES\",\n",
    "    \"BYTES_REV\",\n",
    "    \"MEAN\",\n",
    "    \"MEDIAN\",\n",
    "    \"STDEV\",\n",
    "    \"VAR\",\n",
    "    \"BURSTINESS\",\n",
    "    \"Q1\",\n",
    "    \"Q3\",\n",
    "    \"MIN\",\n",
    "    \"MAX\",\n",
    "    \"MIN_MINUS_MAX\",\n",
    "    \"MODE\",\n",
    "    \"COEFFICIENT_OF_VARIATION\",\n",
    "    \"AVERAGE_DISPERSION\",\n",
    "    \"PERCENT_DEVIATION\",\n",
    "    \"ROOT_MEAN_SQUARE\",\n",
    "    \"PERCENT_BELOW_MEAN\",\n",
    "    \"PERCENT_ABOVE_MEAN\",\n",
    "    \"PEARSON_SK1_SKEWNESS\",\n",
    "    \"PEARSON_SK2_SKEWNESS\",\n",
    "    \"FISHER_MI_3_SKEWNESS\",\n",
    "    \"FISHER_PEARSON_g1_SKEWNESS\",\n",
    "    \"FISHER_PEARSON_G1_SKEWNESS\",\n",
    "    \"GALTON_SKEWNESS\",\n",
    "    \"KURTOSIS\",\n",
    "    \"ENTROPY\",\n",
    "    \"SCALED_ENTROPY\",\n",
    "    \"HURST_EXPONENT\",\n",
    "    \"BENFORD_LAW_PRESENTED\",\n",
    "    \"P_BENFORD\",\n",
    "    \"NORMAL_DISTRIBUTION\",\n",
    "    \"CNT_DISTRIBUTION\",\n",
    "    \"TIME_DISTRIBUTION\",\n",
    "    \"AREA_VALUES_DISTRIBUTION\",\n",
    "    \"MEAN_SCALED_TIME\",\n",
    "    \"MEDIAN_SCALED_TIME\",\n",
    "    \"Q1_SCALED_TIME\",\n",
    "    \"Q3_SCALED_TIME\",\n",
    "    \"DURATION\",\n",
    "    \"MEAN_DIFFTIMES\",\n",
    "    \"MEDIAN_DIFFTIMES\",\n",
    "    \"MIN_DIFFTIMES\",\n",
    "    \"MAX_DIFFTIMES\",\n",
    "    \"MEAN_SCALED_DIFFTIMES\",\n",
    "    \"SIG_SPACES\",\n",
    "    \"SWITCHING_METRIC\",\n",
    "    \"DIRECTIONS\",\n",
    "    \"TRANSIENTS\",\n",
    "    \"CNT_ZEROS\",\n",
    "    \"CNT_NZ_DISTRIBUTION\",\n",
    "    \"BIGGEST_CNT_1_SEC\",\n",
    "    \"PERIODICITY\",\n",
    "    \"VAL\",\n",
    "    \"TIME\",\n",
    "    \"MIN_POWER\",\n",
    "    \"MAX_POWER\",\n",
    "    \"MIN_POWER_FREQ\",\n",
    "    \"MAX_POWER_FREQ\",\n",
    "    \"SPECTRAL_ENERGY\",\n",
    "    \"SPECTRAL_ENTROPY\",\n",
    "    \"SPECTRAL_KURTOSIS\",\n",
    "    \"SPECTRAL_SKEWNESS\",\n",
    "    \"SPECTRAL_ROLLOFF\",\n",
    "    \"SPECTRAL_CENTROID\",\n",
    "    \"SPECTRAL_SPREAD\",\n",
    "    \"SPECTRAL_SLOPE\",\n",
    "    \"SPECTRAL_CREST\",\n",
    "    \"SPECTRAL_FLUX\",\n",
    "    \"SPECTRAL_BANDWIDTH\",\n",
    "    \"PERIODICITY_SCDF\",\n",
    "]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "import sklearn\n",
    "pd.set_option('display.max_columns', None)\n",
    "\n",
    "\n",
    "def handle_df(df):\n",
    "    df['LABEL'] = df.LABEL.astype('category')\n",
    "    df[\"LABEL_code\"] = df[\"LABEL\"].cat.codes\n",
    "\n",
    "    bool_features = [\"TRANSIENTS\", \"BENFORD_LAW_PRESENTED\", \"SIG_SPACES\", \"PERIODICITY\",\"PERIODICITY_SCDF\"]\n",
    "\n",
    "\n",
    "    for F in features:\n",
    "        if F in bool_features:\n",
    "            continue\n",
    "        if F in distribution_features:\n",
    "            df.replace([np.inf], 0.5, inplace=True)\n",
    "            df.replace([-np.inf], 0.5, inplace=True)\n",
    "            df.loc[df[F].isnull(), F] = 0.5\n",
    "        elif F in [\"DIRECTIONS\",\"NORMAL_DISTRIBUTION\"]: \n",
    "            df.replace([np.inf], 0.5, inplace=True)\n",
    "            df.replace([-np.inf], 0.5, inplace=True)\n",
    "            df.loc[df[F].isnull(), F] = 0.5\n",
    "        elif F in frequency_features: \n",
    "            df.replace([np.inf], -1, inplace=True)\n",
    "            df.replace([-np.inf], -1, inplace=True)\n",
    "            df.loc[df[F].isnull(), F] = -1\n",
    "        else:\n",
    "            df.replace([np.inf], 0, inplace=True)\n",
    "            df.replace([-np.inf], 0, inplace=True)\n",
    "            df.loc[df[F].isnull(), F] = 0\n",
    "\n",
    "\n",
    "    for F in bool_features:\n",
    "        df.loc[df[F].isnull(), F] = False\n",
    "        df[F] = df[F].astype('bool')\n",
    "    \n",
    "    return df\n",
    "\n",
    "df = handle_df(df)\n",
    "# df_train = handle_df(df_train)\n",
    "# df_test = handle_df(df_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Unnamed: 0.1</th>\n",
       "      <th>Unnamed: 0</th>\n",
       "      <th>DST_IP</th>\n",
       "      <th>SRC_IP</th>\n",
       "      <th>PACKETS</th>\n",
       "      <th>PACKETS_REV</th>\n",
       "      <th>BYTES</th>\n",
       "      <th>BYTES_REV</th>\n",
       "      <th>TIME_FIRST</th>\n",
       "      <th>TIME_LAST</th>\n",
       "      <th>DST_PORT</th>\n",
       "      <th>SRC_PORT</th>\n",
       "      <th>MEAN</th>\n",
       "      <th>MEDIAN</th>\n",
       "      <th>STDEV</th>\n",
       "      <th>VAR</th>\n",
       "      <th>BURSTINESS</th>\n",
       "      <th>Q1</th>\n",
       "      <th>Q3</th>\n",
       "      <th>MIN</th>\n",
       "      <th>MAX</th>\n",
       "      <th>MIN_MINUS_MAX</th>\n",
       "      <th>MODE</th>\n",
       "      <th>COEFFICIENT_OF_VARIATION</th>\n",
       "      <th>AVERAGE_DISPERSION</th>\n",
       "      <th>PERCENT_DEVIATION</th>\n",
       "      <th>ROOT_MEAN_SQUARE</th>\n",
       "      <th>PERCENT_BELOW_MEAN</th>\n",
       "      <th>PERCENT_ABOVE_MEAN</th>\n",
       "      <th>PEARSON_SK1_SKEWNESS</th>\n",
       "      <th>PEARSON_SK2_SKEWNESS</th>\n",
       "      <th>FISHER_MI_3_SKEWNESS</th>\n",
       "      <th>FISHER_PEARSON_g1_SKEWNESS</th>\n",
       "      <th>FISHER_PEARSON_G1_SKEWNESS</th>\n",
       "      <th>GALTON_SKEWNESS</th>\n",
       "      <th>KURTOSIS</th>\n",
       "      <th>ENTROPY</th>\n",
       "      <th>SCALED_ENTROPY</th>\n",
       "      <th>HURST_EXPONENT</th>\n",
       "      <th>BENFORD_LAW_PRESENTED</th>\n",
       "      <th>P_BENFORD</th>\n",
       "      <th>NORMAL_DISTRIBUTION</th>\n",
       "      <th>CNT_DISTRIBUTION</th>\n",
       "      <th>TIME_DISTRIBUTION</th>\n",
       "      <th>AREA_VALUES_DISTRIBUTION</th>\n",
       "      <th>MEAN_SCALED_TIME</th>\n",
       "      <th>MEDIAN_SCALED_TIME</th>\n",
       "      <th>Q1_SCALED_TIME</th>\n",
       "      <th>Q3_SCALED_TIME</th>\n",
       "      <th>DURATION</th>\n",
       "      <th>MEAN_DIFFTIMES</th>\n",
       "      <th>MEDIAN_DIFFTIMES</th>\n",
       "      <th>MIN_DIFFTIMES</th>\n",
       "      <th>MAX_DIFFTIMES</th>\n",
       "      <th>MEAN_SCALED_DIFFTIMES</th>\n",
       "      <th>SIG_SPACES</th>\n",
       "      <th>SWITCHING_METRIC</th>\n",
       "      <th>TRANSIENTS</th>\n",
       "      <th>CNT_ZEROS</th>\n",
       "      <th>CNT_NZ_DISTRIBUTION</th>\n",
       "      <th>BIGGEST_CNT_1_SEC</th>\n",
       "      <th>DIRECTIONS</th>\n",
       "      <th>PERIODICITY</th>\n",
       "      <th>VAL</th>\n",
       "      <th>TIME</th>\n",
       "      <th>MIN_POWER</th>\n",
       "      <th>MAX_POWER</th>\n",
       "      <th>MIN_POWER_FREQ</th>\n",
       "      <th>MAX_POWER_FREQ</th>\n",
       "      <th>SPECTRAL_ENERGY</th>\n",
       "      <th>SPECTRAL_ENTROPY</th>\n",
       "      <th>SPECTRAL_KURTOSIS</th>\n",
       "      <th>SPECTRAL_SKEWNESS</th>\n",
       "      <th>SPECTRAL_ROLLOFF</th>\n",
       "      <th>SPECTRAL_CENTROID</th>\n",
       "      <th>SPECTRAL_SPREAD</th>\n",
       "      <th>SPECTRAL_SLOPE</th>\n",
       "      <th>SPECTRAL_CREST</th>\n",
       "      <th>SPECTRAL_FLUX</th>\n",
       "      <th>SPECTRAL_BANDWIDTH</th>\n",
       "      <th>PERIODICITY_SCDF</th>\n",
       "      <th>LABEL</th>\n",
       "      <th>LABEL_code</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
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       "      <td>0</td>\n",
       "      <td>216.58.216.142.</td>\n",
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       "      <td>-0.011730</td>\n",
       "      <td>60.0</td>\n",
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       "      <td>1460</td>\n",
       "      <td>60</td>\n",
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       "      <td>553</td>\n",
       "      <td>89.627229</td>\n",
       "      <td>862.836301</td>\n",
       "      <td>0.579710</td>\n",
       "      <td>0.420290</td>\n",
       "      <td>0.924185</td>\n",
       "      <td>2.618248</td>\n",
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       "      <td>3.685169e-09</td>\n",
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       "      <td>3.072657</td>\n",
       "      <td>0.316982</td>\n",
       "      <td>0.691771</td>\n",
       "      <td>True</td>\n",
       "      <td>0.864124</td>\n",
       "      <td>0.123376</td>\n",
       "      <td>0.572893</td>\n",
       "      <td>0.466452</td>\n",
       "      <td>0.830914</td>\n",
       "      <td>138.267585</td>\n",
       "      <td>134.794379</td>\n",
       "      <td>52.199049</td>\n",
       "      <td>220.781038</td>\n",
       "      <td>296.423733</td>\n",
       "      <td>0.358433</td>\n",
       "      <td>0.001376</td>\n",
       "      <td>0.000022</td>\n",
       "      <td>7.800456</td>\n",
       "      <td>0.045950</td>\n",
       "      <td>False</td>\n",
       "      <td>1.649335</td>\n",
       "      <td>True</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.572893</td>\n",
       "      <td>108143</td>\n",
       "      <td>1.0</td>\n",
       "      <td>False</td>\n",
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       "      <td>0.0</td>\n",
       "      <td>2.533836e-08</td>\n",
       "      <td>0.238827</td>\n",
       "      <td>0.054943</td>\n",
       "      <td>0.598495</td>\n",
       "      <td>35.214487</td>\n",
       "      <td>175.621522</td>\n",
       "      <td>261583.407037</td>\n",
       "      <td>32615.831626</td>\n",
       "      <td>0.497969</td>\n",
       "      <td>0.572631</td>\n",
       "      <td>0.215905</td>\n",
       "      <td>0.708048</td>\n",
       "      <td>33.910269</td>\n",
       "      <td>4.108293</td>\n",
       "      <td>0.543552</td>\n",
       "      <td>False</td>\n",
       "      <td>AUDIO</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>10.152.152.11.</td>\n",
       "      <td>216.58.216.142</td>\n",
       "      <td>847</td>\n",
       "      <td>0</td>\n",
       "      <td>74678</td>\n",
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       "      <td>1.437765e+09</td>\n",
       "      <td>1.437765e+09</td>\n",
       "      <td>57361</td>\n",
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       "      <td>148</td>\n",
       "      <td>60.0</td>\n",
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       "      <td>60.0</td>\n",
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       "      <td>60</td>\n",
       "      <td>1520</td>\n",
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       "      <td>60</td>\n",
       "      <td>121.865371</td>\n",
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       "      <td>0.747344</td>\n",
       "      <td>0.252656</td>\n",
       "      <td>0.487911</td>\n",
       "      <td>2.129066</td>\n",
       "      <td>2.528605</td>\n",
       "      <td>2.857451e-08</td>\n",
       "      <td>2.862523e-08</td>\n",
       "      <td>-0.742574</td>\n",
       "      <td>10.427841</td>\n",
       "      <td>2.322060</td>\n",
       "      <td>0.238742</td>\n",
       "      <td>0.698451</td>\n",
       "      <td>False</td>\n",
       "      <td>0.560180</td>\n",
       "      <td>0.303281</td>\n",
       "      <td>0.504819</td>\n",
       "      <td>0.466245</td>\n",
       "      <td>0.970953</td>\n",
       "      <td>138.206084</td>\n",
       "      <td>134.793984</td>\n",
       "      <td>52.287782</td>\n",
       "      <td>219.889171</td>\n",
       "      <td>296.423644</td>\n",
       "      <td>0.350383</td>\n",
       "      <td>0.002776</td>\n",
       "      <td>0.000007</td>\n",
       "      <td>7.800557</td>\n",
       "      <td>0.044918</td>\n",
       "      <td>False</td>\n",
       "      <td>0.912530</td>\n",
       "      <td>False</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.504819</td>\n",
       "      <td>28965</td>\n",
       "      <td>1.0</td>\n",
       "      <td>False</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>6.372675e-08</td>\n",
       "      <td>0.097962</td>\n",
       "      <td>0.288773</td>\n",
       "      <td>0.598892</td>\n",
       "      <td>19.310592</td>\n",
       "      <td>122.818609</td>\n",
       "      <td>228233.785394</td>\n",
       "      <td>29684.738594</td>\n",
       "      <td>0.498565</td>\n",
       "      <td>0.592120</td>\n",
       "      <td>0.234305</td>\n",
       "      <td>0.578221</td>\n",
       "      <td>25.364824</td>\n",
       "      <td>2.249503</td>\n",
       "      <td>0.310119</td>\n",
       "      <td>False</td>\n",
       "      <td>AUDIO</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>10.152.152.11.</td>\n",
       "      <td>173.194.33.97</td>\n",
       "      <td>871</td>\n",
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       "      <td>108133</td>\n",
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       "      <td>1.437765e+09</td>\n",
       "      <td>1.437765e+09</td>\n",
       "      <td>56254</td>\n",
       "      <td>443</td>\n",
       "      <td>184</td>\n",
       "      <td>60.0</td>\n",
       "      <td>282.283545</td>\n",
       "      <td>79684</td>\n",
       "      <td>0.210781</td>\n",
       "      <td>60.0</td>\n",
       "      <td>198.0</td>\n",
       "      <td>60</td>\n",
       "      <td>1520</td>\n",
       "      <td>1460</td>\n",
       "      <td>60</td>\n",
       "      <td>153.414970</td>\n",
       "      <td>162</td>\n",
       "      <td>88.043478</td>\n",
       "      <td>336.903382</td>\n",
       "      <td>0.743972</td>\n",
       "      <td>0.256028</td>\n",
       "      <td>0.439275</td>\n",
       "      <td>1.742928</td>\n",
       "      <td>3.428127</td>\n",
       "      <td>6.584380e-09</td>\n",
       "      <td>6.595744e-09</td>\n",
       "      <td>-0.797101</td>\n",
       "      <td>15.029340</td>\n",
       "      <td>2.657629</td>\n",
       "      <td>0.272116</td>\n",
       "      <td>0.460517</td>\n",
       "      <td>False</td>\n",
       "      <td>0.659239</td>\n",
       "      <td>0.034313</td>\n",
       "      <td>0.550541</td>\n",
       "      <td>0.375514</td>\n",
       "      <td>0.967289</td>\n",
       "      <td>111.241935</td>\n",
       "      <td>92.557258</td>\n",
       "      <td>14.124083</td>\n",
       "      <td>200.482418</td>\n",
       "      <td>296.239266</td>\n",
       "      <td>0.340505</td>\n",
       "      <td>0.006528</td>\n",
       "      <td>0.000005</td>\n",
       "      <td>13.485507</td>\n",
       "      <td>0.025250</td>\n",
       "      <td>False</td>\n",
       "      <td>1.098851</td>\n",
       "      <td>True</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.550541</td>\n",
       "      <td>78137</td>\n",
       "      <td>1.0</td>\n",
       "      <td>False</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.389817e-02</td>\n",
       "      <td>0.105086</td>\n",
       "      <td>0.192420</td>\n",
       "      <td>0.063088</td>\n",
       "      <td>236.099508</td>\n",
       "      <td>1028.916384</td>\n",
       "      <td>17419.211613</td>\n",
       "      <td>3140.992232</td>\n",
       "      <td>0.062492</td>\n",
       "      <td>0.473799</td>\n",
       "      <td>0.277916</td>\n",
       "      <td>-0.076864</td>\n",
       "      <td>2.225462</td>\n",
       "      <td>5.307691</td>\n",
       "      <td>-0.129332</td>\n",
       "      <td>False</td>\n",
       "      <td>AUDIO</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>173.194.33.97.</td>\n",
       "      <td>10.152.152.11</td>\n",
       "      <td>855</td>\n",
       "      <td>0</td>\n",
       "      <td>509135</td>\n",
       "      <td>0</td>\n",
       "      <td>1.437765e+09</td>\n",
       "      <td>1.437765e+09</td>\n",
       "      <td>443</td>\n",
       "      <td>56254</td>\n",
       "      <td>655</td>\n",
       "      <td>333.0</td>\n",
       "      <td>623.441256</td>\n",
       "      <td>388679</td>\n",
       "      <td>-0.024685</td>\n",
       "      <td>60.0</td>\n",
       "      <td>1257.0</td>\n",
       "      <td>60</td>\n",
       "      <td>1520</td>\n",
       "      <td>1460</td>\n",
       "      <td>60</td>\n",
       "      <td>95.181871</td>\n",
       "      <td>591</td>\n",
       "      <td>90.229008</td>\n",
       "      <td>904.366274</td>\n",
       "      <td>0.560234</td>\n",
       "      <td>0.439766</td>\n",
       "      <td>0.954380</td>\n",
       "      <td>2.617729</td>\n",
       "      <td>0.337829</td>\n",
       "      <td>1.978933e-09</td>\n",
       "      <td>1.982413e-09</td>\n",
       "      <td>0.005848</td>\n",
       "      <td>1.333824</td>\n",
       "      <td>2.845553</td>\n",
       "      <td>0.292158</td>\n",
       "      <td>0.567600</td>\n",
       "      <td>True</td>\n",
       "      <td>0.867391</td>\n",
       "      <td>0.092085</td>\n",
       "      <td>0.550418</td>\n",
       "      <td>0.366058</td>\n",
       "      <td>0.881223</td>\n",
       "      <td>108.201270</td>\n",
       "      <td>75.756004</td>\n",
       "      <td>13.469905</td>\n",
       "      <td>199.423162</td>\n",
       "      <td>295.584786</td>\n",
       "      <td>0.346118</td>\n",
       "      <td>0.002929</td>\n",
       "      <td>0.000018</td>\n",
       "      <td>13.522678</td>\n",
       "      <td>0.025595</td>\n",
       "      <td>False</td>\n",
       "      <td>1.536300</td>\n",
       "      <td>True</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.550418</td>\n",
       "      <td>180613</td>\n",
       "      <td>1.0</td>\n",
       "      <td>False</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>8.980974e-05</td>\n",
       "      <td>0.100387</td>\n",
       "      <td>0.839279</td>\n",
       "      <td>0.711735</td>\n",
       "      <td>97.130819</td>\n",
       "      <td>526.574083</td>\n",
       "      <td>30309.061385</td>\n",
       "      <td>6003.374113</td>\n",
       "      <td>0.711139</td>\n",
       "      <td>0.510666</td>\n",
       "      <td>0.278847</td>\n",
       "      <td>0.008315</td>\n",
       "      <td>5.167634</td>\n",
       "      <td>6.112560</td>\n",
       "      <td>-0.127544</td>\n",
       "      <td>False</td>\n",
       "      <td>AUDIO</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>10.152.152.11.</td>\n",
       "      <td>74.125.28.189</td>\n",
       "      <td>81</td>\n",
       "      <td>0</td>\n",
       "      <td>17268</td>\n",
       "      <td>0</td>\n",
       "      <td>1.437765e+09</td>\n",
       "      <td>1.437765e+09</td>\n",
       "      <td>44097</td>\n",
       "      <td>443</td>\n",
       "      <td>273</td>\n",
       "      <td>145.0</td>\n",
       "      <td>301.791319</td>\n",
       "      <td>91078</td>\n",
       "      <td>0.050090</td>\n",
       "      <td>60.0</td>\n",
       "      <td>465.0</td>\n",
       "      <td>60</td>\n",
       "      <td>1056</td>\n",
       "      <td>996</td>\n",
       "      <td>60</td>\n",
       "      <td>110.546271</td>\n",
       "      <td>243</td>\n",
       "      <td>89.010989</td>\n",
       "      <td>405.689384</td>\n",
       "      <td>0.679012</td>\n",
       "      <td>0.320988</td>\n",
       "      <td>0.705786</td>\n",
       "      <td>2.233331</td>\n",
       "      <td>1.313968</td>\n",
       "      <td>6.737302e-09</td>\n",
       "      <td>6.865093e-09</td>\n",
       "      <td>-0.051852</td>\n",
       "      <td>3.515484</td>\n",
       "      <td>2.871809</td>\n",
       "      <td>0.452978</td>\n",
       "      <td>0.534701</td>\n",
       "      <td>False</td>\n",
       "      <td>0.807203</td>\n",
       "      <td>0.636258</td>\n",
       "      <td>0.533125</td>\n",
       "      <td>0.277971</td>\n",
       "      <td>0.802041</td>\n",
       "      <td>76.550766</td>\n",
       "      <td>26.053970</td>\n",
       "      <td>8.732336</td>\n",
       "      <td>100.279453</td>\n",
       "      <td>275.391293</td>\n",
       "      <td>3.442391</td>\n",
       "      <td>0.035526</td>\n",
       "      <td>0.000012</td>\n",
       "      <td>29.708890</td>\n",
       "      <td>0.115871</td>\n",
       "      <td>False</td>\n",
       "      <td>1.350000</td>\n",
       "      <td>True</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.533125</td>\n",
       "      <td>10389</td>\n",
       "      <td>1.0</td>\n",
       "      <td>False</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.338052e-07</td>\n",
       "      <td>0.169611</td>\n",
       "      <td>0.804909</td>\n",
       "      <td>0.942188</td>\n",
       "      <td>124.709379</td>\n",
       "      <td>594.423652</td>\n",
       "      <td>31506.497857</td>\n",
       "      <td>7820.522820</td>\n",
       "      <td>0.940996</td>\n",
       "      <td>0.581749</td>\n",
       "      <td>0.281770</td>\n",
       "      <td>0.321528</td>\n",
       "      <td>6.800252</td>\n",
       "      <td>12.705158</td>\n",
       "      <td>0.137279</td>\n",
       "      <td>False</td>\n",
       "      <td>AUDIO</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>120791</th>\n",
       "      <td>1311</td>\n",
       "      <td>1311</td>\n",
       "      <td>198.52.200.39.</td>\n",
       "      <td>10.0.2.15</td>\n",
       "      <td>12430</td>\n",
       "      <td>0</td>\n",
       "      <td>6689717</td>\n",
       "      <td>0</td>\n",
       "      <td>1.437768e+09</td>\n",
       "      <td>1.437768e+09</td>\n",
       "      <td>443</td>\n",
       "      <td>55139</td>\n",
       "      <td>598</td>\n",
       "      <td>603.0</td>\n",
       "      <td>234.249867</td>\n",
       "      <td>54873</td>\n",
       "      <td>-0.437068</td>\n",
       "      <td>603.0</td>\n",
       "      <td>603.0</td>\n",
       "      <td>60</td>\n",
       "      <td>1520</td>\n",
       "      <td>1460</td>\n",
       "      <td>603</td>\n",
       "      <td>39.172218</td>\n",
       "      <td>86</td>\n",
       "      <td>14.381271</td>\n",
       "      <td>642.418813</td>\n",
       "      <td>0.082060</td>\n",
       "      <td>0.917940</td>\n",
       "      <td>-0.021345</td>\n",
       "      <td>5.084315</td>\n",
       "      <td>1.185365</td>\n",
       "      <td>1.487716e-08</td>\n",
       "      <td>1.487895e-08</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>10.034838</td>\n",
       "      <td>0.823950</td>\n",
       "      <td>0.060578</td>\n",
       "      <td>0.494596</td>\n",
       "      <td>False</td>\n",
       "      <td>0.434457</td>\n",
       "      <td>0.099773</td>\n",
       "      <td>0.645425</td>\n",
       "      <td>0.524006</td>\n",
       "      <td>0.891072</td>\n",
       "      <td>157.189754</td>\n",
       "      <td>158.149459</td>\n",
       "      <td>90.765860</td>\n",
       "      <td>229.011937</td>\n",
       "      <td>299.976789</td>\n",
       "      <td>0.024135</td>\n",
       "      <td>0.026433</td>\n",
       "      <td>0.000015</td>\n",
       "      <td>0.132154</td>\n",
       "      <td>0.182630</td>\n",
       "      <td>False</td>\n",
       "      <td>0.422882</td>\n",
       "      <td>True</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.645425</td>\n",
       "      <td>1653067</td>\n",
       "      <td>1.0</td>\n",
       "      <td>False</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.021118e-09</td>\n",
       "      <td>0.008422</td>\n",
       "      <td>0.463799</td>\n",
       "      <td>0.031897</td>\n",
       "      <td>1.658886</td>\n",
       "      <td>16.482165</td>\n",
       "      <td>165811.630477</td>\n",
       "      <td>24142.132457</td>\n",
       "      <td>0.031103</td>\n",
       "      <td>0.444586</td>\n",
       "      <td>0.320419</td>\n",
       "      <td>-0.333952</td>\n",
       "      <td>25.385595</td>\n",
       "      <td>0.206568</td>\n",
       "      <td>-0.431901</td>\n",
       "      <td>True</td>\n",
       "      <td>VOIP</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>120792</th>\n",
       "      <td>1312</td>\n",
       "      <td>1312</td>\n",
       "      <td>198.52.200.39.</td>\n",
       "      <td>10.0.2.15</td>\n",
       "      <td>13031</td>\n",
       "      <td>0</td>\n",
       "      <td>7268310</td>\n",
       "      <td>0</td>\n",
       "      <td>1.437768e+09</td>\n",
       "      <td>1.437769e+09</td>\n",
       "      <td>443</td>\n",
       "      <td>55139</td>\n",
       "      <td>617</td>\n",
       "      <td>603.0</td>\n",
       "      <td>200.604088</td>\n",
       "      <td>40242</td>\n",
       "      <td>-0.509288</td>\n",
       "      <td>603.0</td>\n",
       "      <td>603.0</td>\n",
       "      <td>60</td>\n",
       "      <td>1520</td>\n",
       "      <td>1460</td>\n",
       "      <td>603</td>\n",
       "      <td>32.512818</td>\n",
       "      <td>69</td>\n",
       "      <td>11.183144</td>\n",
       "      <td>649.522630</td>\n",
       "      <td>0.952651</td>\n",
       "      <td>0.047349</td>\n",
       "      <td>0.069789</td>\n",
       "      <td>6.221209</td>\n",
       "      <td>2.244545</td>\n",
       "      <td>9.546988e-08</td>\n",
       "      <td>9.548087e-08</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>14.665233</td>\n",
       "      <td>0.617473</td>\n",
       "      <td>0.045171</td>\n",
       "      <td>0.539975</td>\n",
       "      <td>False</td>\n",
       "      <td>0.388130</td>\n",
       "      <td>0.020412</td>\n",
       "      <td>0.529469</td>\n",
       "      <td>0.500055</td>\n",
       "      <td>0.915016</td>\n",
       "      <td>150.014497</td>\n",
       "      <td>149.894488</td>\n",
       "      <td>74.708720</td>\n",
       "      <td>225.460399</td>\n",
       "      <td>299.995767</td>\n",
       "      <td>0.023023</td>\n",
       "      <td>0.026841</td>\n",
       "      <td>0.000009</td>\n",
       "      <td>0.113963</td>\n",
       "      <td>0.202026</td>\n",
       "      <td>False</td>\n",
       "      <td>0.269685</td>\n",
       "      <td>False</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.529469</td>\n",
       "      <td>1615422</td>\n",
       "      <td>1.0</td>\n",
       "      <td>False</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>9.407111e-09</td>\n",
       "      <td>0.012832</td>\n",
       "      <td>0.180897</td>\n",
       "      <td>0.098451</td>\n",
       "      <td>1.849477</td>\n",
       "      <td>17.423927</td>\n",
       "      <td>253869.854750</td>\n",
       "      <td>30044.784781</td>\n",
       "      <td>0.097656</td>\n",
       "      <td>0.478155</td>\n",
       "      <td>0.320866</td>\n",
       "      <td>0.029524</td>\n",
       "      <td>34.689759</td>\n",
       "      <td>0.221259</td>\n",
       "      <td>-0.082447</td>\n",
       "      <td>True</td>\n",
       "      <td>VOIP</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>120793</th>\n",
       "      <td>1313</td>\n",
       "      <td>1313</td>\n",
       "      <td>10.0.2.15.</td>\n",
       "      <td>198.52.200.39</td>\n",
       "      <td>16889</td>\n",
       "      <td>0</td>\n",
       "      <td>3854617</td>\n",
       "      <td>0</td>\n",
       "      <td>1.437768e+09</td>\n",
       "      <td>1.437769e+09</td>\n",
       "      <td>55139</td>\n",
       "      <td>443</td>\n",
       "      <td>288</td>\n",
       "      <td>60.0</td>\n",
       "      <td>421.268323</td>\n",
       "      <td>177467</td>\n",
       "      <td>0.187895</td>\n",
       "      <td>60.0</td>\n",
       "      <td>351.0</td>\n",
       "      <td>60</td>\n",
       "      <td>1480</td>\n",
       "      <td>1420</td>\n",
       "      <td>60</td>\n",
       "      <td>146.273723</td>\n",
       "      <td>332</td>\n",
       "      <td>115.277778</td>\n",
       "      <td>510.425780</td>\n",
       "      <td>0.729173</td>\n",
       "      <td>0.270827</td>\n",
       "      <td>0.541223</td>\n",
       "      <td>1.908522</td>\n",
       "      <td>1.643574</td>\n",
       "      <td>3.108560e-09</td>\n",
       "      <td>3.108837e-09</td>\n",
       "      <td>-0.567010</td>\n",
       "      <td>4.202331</td>\n",
       "      <td>1.484730</td>\n",
       "      <td>0.105721</td>\n",
       "      <td>0.532216</td>\n",
       "      <td>False</td>\n",
       "      <td>0.572656</td>\n",
       "      <td>0.013398</td>\n",
       "      <td>0.499628</td>\n",
       "      <td>0.498071</td>\n",
       "      <td>0.950072</td>\n",
       "      <td>149.420427</td>\n",
       "      <td>149.282066</td>\n",
       "      <td>74.871467</td>\n",
       "      <td>223.941135</td>\n",
       "      <td>299.998091</td>\n",
       "      <td>0.017764</td>\n",
       "      <td>0.017104</td>\n",
       "      <td>0.000005</td>\n",
       "      <td>0.113980</td>\n",
       "      <td>0.155852</td>\n",
       "      <td>False</td>\n",
       "      <td>1.052108</td>\n",
       "      <td>True</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.499628</td>\n",
       "      <td>1032704</td>\n",
       "      <td>1.0</td>\n",
       "      <td>False</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>7.078245e-09</td>\n",
       "      <td>0.001082</td>\n",
       "      <td>0.649552</td>\n",
       "      <td>0.009249</td>\n",
       "      <td>0.202239</td>\n",
       "      <td>2.786366</td>\n",
       "      <td>603625.727862</td>\n",
       "      <td>43381.672901</td>\n",
       "      <td>0.008653</td>\n",
       "      <td>0.445179</td>\n",
       "      <td>0.307234</td>\n",
       "      <td>-0.157668</td>\n",
       "      <td>26.758707</td>\n",
       "      <td>0.023137</td>\n",
       "      <td>-0.640303</td>\n",
       "      <td>True</td>\n",
       "      <td>VOIP</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>120794</th>\n",
       "      <td>1314</td>\n",
       "      <td>1314</td>\n",
       "      <td>198.52.200.39.</td>\n",
       "      <td>10.0.2.15</td>\n",
       "      <td>1074</td>\n",
       "      <td>0</td>\n",
       "      <td>608083</td>\n",
       "      <td>0</td>\n",
       "      <td>1.437769e+09</td>\n",
       "      <td>1.437769e+09</td>\n",
       "      <td>443</td>\n",
       "      <td>55139</td>\n",
       "      <td>626</td>\n",
       "      <td>603.0</td>\n",
       "      <td>203.177263</td>\n",
       "      <td>41281</td>\n",
       "      <td>-0.509930</td>\n",
       "      <td>603.0</td>\n",
       "      <td>603.0</td>\n",
       "      <td>60</td>\n",
       "      <td>1520</td>\n",
       "      <td>1460</td>\n",
       "      <td>603</td>\n",
       "      <td>32.456432</td>\n",
       "      <td>77</td>\n",
       "      <td>12.300319</td>\n",
       "      <td>658.293949</td>\n",
       "      <td>0.945996</td>\n",
       "      <td>0.054004</td>\n",
       "      <td>0.113202</td>\n",
       "      <td>6.275308</td>\n",
       "      <td>2.435887</td>\n",
       "      <td>2.209141e-08</td>\n",
       "      <td>2.212232e-08</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>14.538439</td>\n",
       "      <td>0.616706</td>\n",
       "      <td>0.061249</td>\n",
       "      <td>0.577962</td>\n",
       "      <td>False</td>\n",
       "      <td>0.387157</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.511472</td>\n",
       "      <td>0.869841</td>\n",
       "      <td>12.647428</td>\n",
       "      <td>13.031190</td>\n",
       "      <td>6.546725</td>\n",
       "      <td>18.894091</td>\n",
       "      <td>24.727524</td>\n",
       "      <td>0.023045</td>\n",
       "      <td>0.027997</td>\n",
       "      <td>0.000068</td>\n",
       "      <td>0.076411</td>\n",
       "      <td>0.301596</td>\n",
       "      <td>False</td>\n",
       "      <td>0.255359</td>\n",
       "      <td>False</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>672523</td>\n",
       "      <td>1.0</td>\n",
       "      <td>False</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.278024e-05</td>\n",
       "      <td>0.019340</td>\n",
       "      <td>0.967816</td>\n",
       "      <td>0.137985</td>\n",
       "      <td>23.570576</td>\n",
       "      <td>168.408014</td>\n",
       "      <td>18617.916233</td>\n",
       "      <td>5826.009980</td>\n",
       "      <td>0.129045</td>\n",
       "      <td>0.392288</td>\n",
       "      <td>0.269686</td>\n",
       "      <td>-0.597276</td>\n",
       "      <td>4.102470</td>\n",
       "      <td>0.173548</td>\n",
       "      <td>-0.829831</td>\n",
       "      <td>False</td>\n",
       "      <td>VOIP</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>120795</th>\n",
       "      <td>1315</td>\n",
       "      <td>1315</td>\n",
       "      <td>10.0.2.15.</td>\n",
       "      <td>198.52.200.39</td>\n",
       "      <td>1368</td>\n",
       "      <td>0</td>\n",
       "      <td>290990</td>\n",
       "      <td>0</td>\n",
       "      <td>1.437769e+09</td>\n",
       "      <td>1.437769e+09</td>\n",
       "      <td>55139</td>\n",
       "      <td>443</td>\n",
       "      <td>272</td>\n",
       "      <td>60.0</td>\n",
       "      <td>408.432369</td>\n",
       "      <td>166818</td>\n",
       "      <td>0.200508</td>\n",
       "      <td>60.0</td>\n",
       "      <td>351.0</td>\n",
       "      <td>60</td>\n",
       "      <td>1480</td>\n",
       "      <td>1420</td>\n",
       "      <td>60</td>\n",
       "      <td>150.158959</td>\n",
       "      <td>316</td>\n",
       "      <td>116.176471</td>\n",
       "      <td>490.986340</td>\n",
       "      <td>0.745614</td>\n",
       "      <td>0.254386</td>\n",
       "      <td>0.519058</td>\n",
       "      <td>1.850980</td>\n",
       "      <td>1.748988</td>\n",
       "      <td>1.044991e-08</td>\n",
       "      <td>1.046138e-08</td>\n",
       "      <td>-0.457045</td>\n",
       "      <td>4.592140</td>\n",
       "      <td>1.410114</td>\n",
       "      <td>0.135356</td>\n",
       "      <td>0.603204</td>\n",
       "      <td>False</td>\n",
       "      <td>0.555050</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.508712</td>\n",
       "      <td>0.889239</td>\n",
       "      <td>12.579245</td>\n",
       "      <td>12.850368</td>\n",
       "      <td>6.493582</td>\n",
       "      <td>18.682703</td>\n",
       "      <td>24.727639</td>\n",
       "      <td>0.018089</td>\n",
       "      <td>0.018290</td>\n",
       "      <td>0.000010</td>\n",
       "      <td>0.062125</td>\n",
       "      <td>0.291171</td>\n",
       "      <td>False</td>\n",
       "      <td>0.981712</td>\n",
       "      <td>True</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>373070</td>\n",
       "      <td>1.0</td>\n",
       "      <td>False</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4.383140e-06</td>\n",
       "      <td>0.002418</td>\n",
       "      <td>0.392875</td>\n",
       "      <td>0.593329</td>\n",
       "      <td>2.814611</td>\n",
       "      <td>29.044726</td>\n",
       "      <td>29348.535887</td>\n",
       "      <td>7826.834605</td>\n",
       "      <td>0.580813</td>\n",
       "      <td>0.540675</td>\n",
       "      <td>0.266813</td>\n",
       "      <td>0.049221</td>\n",
       "      <td>4.294642</td>\n",
       "      <td>0.022102</td>\n",
       "      <td>0.200455</td>\n",
       "      <td>True</td>\n",
       "      <td>VOIP</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>120796 rows × 83 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        Unnamed: 0.1  Unnamed: 0           DST_IP          SRC_IP  PACKETS  \\\n",
       "0                  0           0  216.58.216.142.   10.152.152.11      828   \n",
       "1                  1           1   10.152.152.11.  216.58.216.142      847   \n",
       "2                  2           2   10.152.152.11.   173.194.33.97      871   \n",
       "3                  3           3   173.194.33.97.   10.152.152.11      855   \n",
       "4                  4           4   10.152.152.11.   74.125.28.189       81   \n",
       "...              ...         ...              ...             ...      ...   \n",
       "120791          1311        1311   198.52.200.39.       10.0.2.15    12430   \n",
       "120792          1312        1312   198.52.200.39.       10.0.2.15    13031   \n",
       "120793          1313        1313       10.0.2.15.   198.52.200.39    16889   \n",
       "120794          1314        1314   198.52.200.39.       10.0.2.15     1074   \n",
       "120795          1315        1315       10.0.2.15.   198.52.200.39     1368   \n",
       "\n",
       "        PACKETS_REV    BYTES  BYTES_REV    TIME_FIRST     TIME_LAST  DST_PORT  \\\n",
       "0                 0   461864          0  1.437765e+09  1.437765e+09       443   \n",
       "1                 0    74678          0  1.437765e+09  1.437765e+09     57361   \n",
       "2                 0   108133          0  1.437765e+09  1.437765e+09     56254   \n",
       "3                 0   509135          0  1.437765e+09  1.437765e+09       443   \n",
       "4                 0    17268          0  1.437765e+09  1.437765e+09     44097   \n",
       "...             ...      ...        ...           ...           ...       ...   \n",
       "120791            0  6689717          0  1.437768e+09  1.437768e+09       443   \n",
       "120792            0  7268310          0  1.437768e+09  1.437769e+09       443   \n",
       "120793            0  3854617          0  1.437768e+09  1.437769e+09     55139   \n",
       "120794            0   608083          0  1.437769e+09  1.437769e+09       443   \n",
       "120795            0   290990          0  1.437769e+09  1.437769e+09     55139   \n",
       "\n",
       "        SRC_PORT  MEAN  MEDIAN       STDEV     VAR  BURSTINESS     Q1      Q3  \\\n",
       "0          57361   617   273.0  602.693123  363240   -0.011730   60.0  1517.0   \n",
       "1            443   148    60.0  180.360750   32531    0.098552   60.0   161.0   \n",
       "2            443   184    60.0  282.283545   79684    0.210781   60.0   198.0   \n",
       "3          56254   655   333.0  623.441256  388679   -0.024685   60.0  1257.0   \n",
       "4            443   273   145.0  301.791319   91078    0.050090   60.0   465.0   \n",
       "...          ...   ...     ...         ...     ...         ...    ...     ...   \n",
       "120791     55139   598   603.0  234.249867   54873   -0.437068  603.0   603.0   \n",
       "120792     55139   617   603.0  200.604088   40242   -0.509288  603.0   603.0   \n",
       "120793       443   288    60.0  421.268323  177467    0.187895   60.0   351.0   \n",
       "120794     55139   626   603.0  203.177263   41281   -0.509930  603.0   603.0   \n",
       "120795       443   272    60.0  408.432369  166818    0.200508   60.0   351.0   \n",
       "\n",
       "        MIN   MAX  MIN_MINUS_MAX  MODE  COEFFICIENT_OF_VARIATION  \\\n",
       "0        60  1520           1460    60                 97.681219   \n",
       "1        60  1520           1460    60                121.865371   \n",
       "2        60  1520           1460    60                153.414970   \n",
       "3        60  1520           1460    60                 95.181871   \n",
       "4        60  1056            996    60                110.546271   \n",
       "...     ...   ...            ...   ...                       ...   \n",
       "120791   60  1520           1460   603                 39.172218   \n",
       "120792   60  1520           1460   603                 32.512818   \n",
       "120793   60  1480           1420    60                146.273723   \n",
       "120794   60  1520           1460   603                 32.456432   \n",
       "120795   60  1480           1420    60                150.158959   \n",
       "\n",
       "        AVERAGE_DISPERSION  PERCENT_DEVIATION  ROOT_MEAN_SQUARE  \\\n",
       "0                      553          89.627229        862.836301   \n",
       "1                      123          83.108108        233.337173   \n",
       "2                      162          88.043478        336.903382   \n",
       "3                      591          90.229008        904.366274   \n",
       "4                      243          89.010989        405.689384   \n",
       "...                    ...                ...               ...   \n",
       "120791                  86          14.381271        642.418813   \n",
       "120792                  69          11.183144        649.522630   \n",
       "120793                 332         115.277778        510.425780   \n",
       "120794                  77          12.300319        658.293949   \n",
       "120795                 316         116.176471        490.986340   \n",
       "\n",
       "        PERCENT_BELOW_MEAN  PERCENT_ABOVE_MEAN  PEARSON_SK1_SKEWNESS  \\\n",
       "0                 0.579710            0.420290              0.924185   \n",
       "1                 0.747344            0.252656              0.487911   \n",
       "2                 0.743972            0.256028              0.439275   \n",
       "3                 0.560234            0.439766              0.954380   \n",
       "4                 0.679012            0.320988              0.705786   \n",
       "...                    ...                 ...                   ...   \n",
       "120791            0.082060            0.917940             -0.021345   \n",
       "120792            0.952651            0.047349              0.069789   \n",
       "120793            0.729173            0.270827              0.541223   \n",
       "120794            0.945996            0.054004              0.113202   \n",
       "120795            0.745614            0.254386              0.519058   \n",
       "\n",
       "        PEARSON_SK2_SKEWNESS  FISHER_MI_3_SKEWNESS  \\\n",
       "0                   2.618248              0.558478   \n",
       "1                   2.129066              2.528605   \n",
       "2                   1.742928              3.428127   \n",
       "3                   2.617729              0.337829   \n",
       "4                   2.233331              1.313968   \n",
       "...                      ...                   ...   \n",
       "120791              5.084315              1.185365   \n",
       "120792              6.221209              2.244545   \n",
       "120793              1.908522              1.643574   \n",
       "120794              6.275308              2.435887   \n",
       "120795              1.850980              1.748988   \n",
       "\n",
       "        FISHER_PEARSON_g1_SKEWNESS  FISHER_PEARSON_G1_SKEWNESS  \\\n",
       "0                     3.685169e-09                3.691861e-09   \n",
       "1                     2.857451e-08                2.862523e-08   \n",
       "2                     6.584380e-09                6.595744e-09   \n",
       "3                     1.978933e-09                1.982413e-09   \n",
       "4                     6.737302e-09                6.865093e-09   \n",
       "...                            ...                         ...   \n",
       "120791                1.487716e-08                1.487895e-08   \n",
       "120792                9.546988e-08                9.548087e-08   \n",
       "120793                3.108560e-09                3.108837e-09   \n",
       "120794                2.209141e-08                2.212232e-08   \n",
       "120795                1.044991e-08                1.046138e-08   \n",
       "\n",
       "        GALTON_SKEWNESS   KURTOSIS   ENTROPY  SCALED_ENTROPY  HURST_EXPONENT  \\\n",
       "0              0.235415   1.600780  3.072657        0.316982        0.691771   \n",
       "1             -0.742574  10.427841  2.322060        0.238742        0.698451   \n",
       "2             -0.797101  15.029340  2.657629        0.272116        0.460517   \n",
       "3              0.005848   1.333824  2.845553        0.292158        0.567600   \n",
       "4             -0.051852   3.515484  2.871809        0.452978        0.534701   \n",
       "...                 ...        ...       ...             ...             ...   \n",
       "120791         0.000000  10.034838  0.823950        0.060578        0.494596   \n",
       "120792         0.000000  14.665233  0.617473        0.045171        0.539975   \n",
       "120793        -0.567010   4.202331  1.484730        0.105721        0.532216   \n",
       "120794         0.000000  14.538439  0.616706        0.061249        0.577962   \n",
       "120795        -0.457045   4.592140  1.410114        0.135356        0.603204   \n",
       "\n",
       "        BENFORD_LAW_PRESENTED  P_BENFORD  NORMAL_DISTRIBUTION  \\\n",
       "0                        True   0.864124             0.123376   \n",
       "1                       False   0.560180             0.303281   \n",
       "2                       False   0.659239             0.034313   \n",
       "3                        True   0.867391             0.092085   \n",
       "4                       False   0.807203             0.636258   \n",
       "...                       ...        ...                  ...   \n",
       "120791                  False   0.434457             0.099773   \n",
       "120792                  False   0.388130             0.020412   \n",
       "120793                  False   0.572656             0.013398   \n",
       "120794                  False   0.387157             0.000000   \n",
       "120795                  False   0.555050             0.000000   \n",
       "\n",
       "        CNT_DISTRIBUTION  TIME_DISTRIBUTION  AREA_VALUES_DISTRIBUTION  \\\n",
       "0               0.572893           0.466452                  0.830914   \n",
       "1               0.504819           0.466245                  0.970953   \n",
       "2               0.550541           0.375514                  0.967289   \n",
       "3               0.550418           0.366058                  0.881223   \n",
       "4               0.533125           0.277971                  0.802041   \n",
       "...                  ...                ...                       ...   \n",
       "120791          0.645425           0.524006                  0.891072   \n",
       "120792          0.529469           0.500055                  0.915016   \n",
       "120793          0.499628           0.498071                  0.950072   \n",
       "120794          0.000000           0.511472                  0.869841   \n",
       "120795          0.000000           0.508712                  0.889239   \n",
       "\n",
       "        MEAN_SCALED_TIME  MEDIAN_SCALED_TIME  Q1_SCALED_TIME  Q3_SCALED_TIME  \\\n",
       "0             138.267585          134.794379       52.199049      220.781038   \n",
       "1             138.206084          134.793984       52.287782      219.889171   \n",
       "2             111.241935           92.557258       14.124083      200.482418   \n",
       "3             108.201270           75.756004       13.469905      199.423162   \n",
       "4              76.550766           26.053970        8.732336      100.279453   \n",
       "...                  ...                 ...             ...             ...   \n",
       "120791        157.189754          158.149459       90.765860      229.011937   \n",
       "120792        150.014497          149.894488       74.708720      225.460399   \n",
       "120793        149.420427          149.282066       74.871467      223.941135   \n",
       "120794         12.647428           13.031190        6.546725       18.894091   \n",
       "120795         12.579245           12.850368        6.493582       18.682703   \n",
       "\n",
       "          DURATION  MEAN_DIFFTIMES  MEDIAN_DIFFTIMES  MIN_DIFFTIMES  \\\n",
       "0       296.423733        0.358433          0.001376       0.000022   \n",
       "1       296.423644        0.350383          0.002776       0.000007   \n",
       "2       296.239266        0.340505          0.006528       0.000005   \n",
       "3       295.584786        0.346118          0.002929       0.000018   \n",
       "4       275.391293        3.442391          0.035526       0.000012   \n",
       "...            ...             ...               ...            ...   \n",
       "120791  299.976789        0.024135          0.026433       0.000015   \n",
       "120792  299.995767        0.023023          0.026841       0.000009   \n",
       "120793  299.998091        0.017764          0.017104       0.000005   \n",
       "120794   24.727524        0.023045          0.027997       0.000068   \n",
       "120795   24.727639        0.018089          0.018290       0.000010   \n",
       "\n",
       "        MAX_DIFFTIMES  MEAN_SCALED_DIFFTIMES  SIG_SPACES  SWITCHING_METRIC  \\\n",
       "0            7.800456               0.045950       False          1.649335   \n",
       "1            7.800557               0.044918       False          0.912530   \n",
       "2           13.485507               0.025250       False          1.098851   \n",
       "3           13.522678               0.025595       False          1.536300   \n",
       "4           29.708890               0.115871       False          1.350000   \n",
       "...               ...                    ...         ...               ...   \n",
       "120791       0.132154               0.182630       False          0.422882   \n",
       "120792       0.113963               0.202026       False          0.269685   \n",
       "120793       0.113980               0.155852       False          1.052108   \n",
       "120794       0.076411               0.301596       False          0.255359   \n",
       "120795       0.062125               0.291171       False          0.981712   \n",
       "\n",
       "        TRANSIENTS  CNT_ZEROS  CNT_NZ_DISTRIBUTION  BIGGEST_CNT_1_SEC  \\\n",
       "0             True        0.0             0.572893             108143   \n",
       "1            False        0.0             0.504819              28965   \n",
       "2             True        0.0             0.550541              78137   \n",
       "3             True        0.0             0.550418             180613   \n",
       "4             True        0.0             0.533125              10389   \n",
       "...            ...        ...                  ...                ...   \n",
       "120791        True        0.0             0.645425            1653067   \n",
       "120792       False        0.0             0.529469            1615422   \n",
       "120793        True        0.0             0.499628            1032704   \n",
       "120794       False        0.0             0.000000             672523   \n",
       "120795        True        0.0             0.000000             373070   \n",
       "\n",
       "        DIRECTIONS  PERIODICITY  VAL  TIME     MIN_POWER  MAX_POWER  \\\n",
       "0              1.0        False    0   0.0  2.533836e-08   0.238827   \n",
       "1              1.0        False    0   0.0  6.372675e-08   0.097962   \n",
       "2              1.0        False    0   0.0  1.389817e-02   0.105086   \n",
       "3              1.0        False    0   0.0  8.980974e-05   0.100387   \n",
       "4              1.0        False    0   0.0  2.338052e-07   0.169611   \n",
       "...            ...          ...  ...   ...           ...        ...   \n",
       "120791         1.0        False    0   0.0  2.021118e-09   0.008422   \n",
       "120792         1.0        False    0   0.0  9.407111e-09   0.012832   \n",
       "120793         1.0        False    0   0.0  7.078245e-09   0.001082   \n",
       "120794         1.0        False    0   0.0  1.278024e-05   0.019340   \n",
       "120795         1.0        False    0   0.0  4.383140e-06   0.002418   \n",
       "\n",
       "        MIN_POWER_FREQ  MAX_POWER_FREQ  SPECTRAL_ENERGY  SPECTRAL_ENTROPY  \\\n",
       "0             0.054943        0.598495        35.214487        175.621522   \n",
       "1             0.288773        0.598892        19.310592        122.818609   \n",
       "2             0.192420        0.063088       236.099508       1028.916384   \n",
       "3             0.839279        0.711735        97.130819        526.574083   \n",
       "4             0.804909        0.942188       124.709379        594.423652   \n",
       "...                ...             ...              ...               ...   \n",
       "120791        0.463799        0.031897         1.658886         16.482165   \n",
       "120792        0.180897        0.098451         1.849477         17.423927   \n",
       "120793        0.649552        0.009249         0.202239          2.786366   \n",
       "120794        0.967816        0.137985        23.570576        168.408014   \n",
       "120795        0.392875        0.593329         2.814611         29.044726   \n",
       "\n",
       "        SPECTRAL_KURTOSIS  SPECTRAL_SKEWNESS  SPECTRAL_ROLLOFF  \\\n",
       "0           261583.407037       32615.831626          0.497969   \n",
       "1           228233.785394       29684.738594          0.498565   \n",
       "2            17419.211613        3140.992232          0.062492   \n",
       "3            30309.061385        6003.374113          0.711139   \n",
       "4            31506.497857        7820.522820          0.940996   \n",
       "...                   ...                ...               ...   \n",
       "120791      165811.630477       24142.132457          0.031103   \n",
       "120792      253869.854750       30044.784781          0.097656   \n",
       "120793      603625.727862       43381.672901          0.008653   \n",
       "120794       18617.916233        5826.009980          0.129045   \n",
       "120795       29348.535887        7826.834605          0.580813   \n",
       "\n",
       "        SPECTRAL_CENTROID  SPECTRAL_SPREAD  SPECTRAL_SLOPE  SPECTRAL_CREST  \\\n",
       "0                0.572631         0.215905        0.708048       33.910269   \n",
       "1                0.592120         0.234305        0.578221       25.364824   \n",
       "2                0.473799         0.277916       -0.076864        2.225462   \n",
       "3                0.510666         0.278847        0.008315        5.167634   \n",
       "4                0.581749         0.281770        0.321528        6.800252   \n",
       "...                   ...              ...             ...             ...   \n",
       "120791           0.444586         0.320419       -0.333952       25.385595   \n",
       "120792           0.478155         0.320866        0.029524       34.689759   \n",
       "120793           0.445179         0.307234       -0.157668       26.758707   \n",
       "120794           0.392288         0.269686       -0.597276        4.102470   \n",
       "120795           0.540675         0.266813        0.049221        4.294642   \n",
       "\n",
       "        SPECTRAL_FLUX  SPECTRAL_BANDWIDTH  PERIODICITY_SCDF  LABEL  LABEL_code  \n",
       "0            4.108293            0.543552             False  AUDIO           0  \n",
       "1            2.249503            0.310119             False  AUDIO           0  \n",
       "2            5.307691           -0.129332             False  AUDIO           0  \n",
       "3            6.112560           -0.127544             False  AUDIO           0  \n",
       "4           12.705158            0.137279             False  AUDIO           0  \n",
       "...               ...                 ...               ...    ...         ...  \n",
       "120791       0.206568           -0.431901              True   VOIP           7  \n",
       "120792       0.221259           -0.082447              True   VOIP           7  \n",
       "120793       0.023137           -0.640303              True   VOIP           7  \n",
       "120794       0.173548           -0.829831             False   VOIP           7  \n",
       "120795       0.022102            0.200455              True   VOIP           7  \n",
       "\n",
       "[120796 rows x 83 columns]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>LABEL</th>\n",
       "      <th>LABEL_code</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>AUDIO</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3440</th>\n",
       "      <td>BROWSING</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50987</th>\n",
       "      <td>CHAT</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>51590</th>\n",
       "      <td>FILE_TRANSFER</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>54940</th>\n",
       "      <td>MAIL</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>55395</th>\n",
       "      <td>P2P</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>114901</th>\n",
       "      <td>VIDEO</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>118281</th>\n",
       "      <td>VOIP</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                LABEL  LABEL_code\n",
       "0               AUDIO           0\n",
       "3440         BROWSING           1\n",
       "50987            CHAT           2\n",
       "51590   FILE_TRANSFER           3\n",
       "54940            MAIL           4\n",
       "55395             P2P           5\n",
       "114901          VIDEO           6\n",
       "118281           VOIP           7"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[[\"LABEL\", \"LABEL_code\"]].drop_duplicates().sort_values(\"LABEL_code\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['AUDIO', 'BROWSING', 'CHAT', 'FILE_TRANSFER', 'MAIL', 'P2P', 'VIDEO', 'VOIP']"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "classifications_array = []\n",
    "for index, row in df[[\"LABEL\", \"LABEL_code\"]].drop_duplicates().sort_values(\"LABEL_code\").iterrows():\n",
    "    classifications_array.append(row[0])\n",
    "classifications_array"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = df[[\"LABEL_code\"] + features].copy()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "def clean_dataset(df):\n",
    "    assert isinstance(df, pd.DataFrame), \"df needs to be a pd.DataFrame\"\n",
    "    df.dropna(inplace=True)\n",
    "    indices_to_keep = ~df.isin([np.nan, np.inf, -np.inf]).any(1)\n",
    "    return df[indices_to_keep].astype(np.float64)\n",
    "\n",
    "df = clean_dataset(df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(120796, 74)"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_validation = df.sample(n = 20000)\n",
    "df_features =  df[~df.isin(df_validation)].dropna()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_confusion_matrix(y_test, y_pred):\n",
    "    # Get and reshape confusion matrix data\n",
    "    matrix = confusion_matrix(y_test, y_pred)\n",
    "    percentage_matrix = matrix.astype('float') / matrix.sum(axis=1)[:, np.newaxis]\n",
    "    return matrix, percentage_matrix\n",
    "\n",
    "def plot_confusion_matrix(matrix, percentage_matrix, model=\"\"):\n",
    "    # Build the plot\n",
    "    fig, ax = plt.subplots(1, 2,figsize=(15,5))\n",
    "    sns.set(font_scale=1.4)\n",
    "    sns.heatmap(matrix, annot=True, annot_kws={'size':10}, fmt='g',\n",
    "                cmap=plt.cm.Greens, linewidths=0.2, ax=ax[0])\n",
    "    sns.heatmap(percentage_matrix, annot=True, annot_kws={'size':10}, fmt='g',\n",
    "                cmap=plt.cm.Greens, linewidths=0.2, ax=ax[1])\n",
    "    # Add labels to the plot\n",
    "    plt.tick_params(axis='both', which='minor', labelsize=5)\n",
    "    # tick_marks = np.arange(len(classifications_array)) + 0.5\n",
    "    # plt.xticks(tick_marks, classifications_array, rotation=85)\n",
    "    # plt.yticks(tick_marks, classifications_array, rotation=0)\n",
    "    ax[0].set_xlabel('Predicted label')\n",
    "    ax[0].set_ylabel('True label')\n",
    "    ax[0].set_title(f'Absolute Confusion Matrix for {model}')\n",
    "    ax[1].set_xlabel('Predicted label')\n",
    "    ax[1].set_ylabel('True label')\n",
    "    ax[1].set_title(f'Relative Confusion Matrix for {model}')\n",
    "    # pyplot.savefig(\"ddos_timeseries_plugin_classification.eps\", format=\"eps\")\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "X = df[features]\n",
    "y = df.LABEL_code\n",
    "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.3, stratify=y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "5.0    41811\n",
       "1.0    33469\n",
       "0.0     2589\n",
       "6.0     2440\n",
       "3.0     2407\n",
       "7.0      996\n",
       "2.0      500\n",
       "4.0      345\n",
       "Name: LABEL_code, dtype: int64"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y_train.value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "5.0    17919\n",
       "1.0    14344\n",
       "0.0     1109\n",
       "6.0     1046\n",
       "3.0     1031\n",
       "7.0      427\n",
       "2.0      215\n",
       "4.0      148\n",
       "Name: LABEL_code, dtype: int64"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y_test.value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "from hyperopt import STATUS_OK, Trials, fmin, hp, tpe\n",
    "from sklearn.metrics import mean_absolute_error\n",
    "\n",
    "def tunne_together_XGBoost_classification(df_tunne, _features, verbose=True):\n",
    "    X=df_tunne[_features]  # Features\n",
    "    y=df_tunne['LABEL_code']  # Labels\n",
    "    X_train, X_test, y_train, y_test = train_test_split(X, y, test_size = 0.3, random_state = 0, stratify=y)\n",
    "    \n",
    "    def objective(space):\n",
    "        clf = XGBClassifier(\n",
    "                        n_estimators = int(space['n_estimators']), max_depth = int(space['max_depth']), gamma = space['gamma'],\n",
    "                        reg_alpha = int(space['reg_alpha']),min_child_weight=int(space['min_child_weight']),\n",
    "                        colsample_bytree=int(space['colsample_bytree']), \n",
    "                        # subsample=int(space['subsample']),\n",
    "                        # eta=space['eta'],\n",
    "                            )\n",
    "\n",
    "        evaluation = [( X_train, y_train), ( X_test, y_test)]\n",
    "\n",
    "        clf.fit(X_train, y_train,\n",
    "                eval_set=evaluation, eval_metric=\"auc\",\n",
    "                early_stopping_rounds=10,verbose=False)\n",
    "\n",
    "        pred = clf.predict(X_test)\n",
    "        # accuracy = mean_absolute_error(y_test, pred)\n",
    "        # accuracy = accuracy_score(y_test, pred)\n",
    "        accuracy = f1_score(y_test, pred,average='weighted')\n",
    "        if verbose is True:\n",
    "            print (\"SCORE:\", accuracy, \"  \", space)\n",
    "        return {'loss': -accuracy, 'status': STATUS_OK }\n",
    "    \n",
    "    space={'max_depth': hp.quniform(\"max_depth\", 5, 30, 4),\n",
    "        'gamma': hp.uniform ('gamma', 1,4),\n",
    "        'reg_alpha' : hp.quniform('reg_alpha', 0,200,5),\n",
    "        'reg_lambda' : hp.uniform('reg_lambda', 0,1),\n",
    "        'colsample_bytree' : hp.uniform('colsample_bytree', 0, 1),\n",
    "        'min_child_weight' : hp.quniform('min_child_weight', 0, 20, 2),\n",
    "        'n_estimators': hp.quniform('n_estimators', 50, 500, 50),\n",
    "        # 'subsample': hp.quniform('subsample', 3, 20, 1),\n",
    "        # 'eta': hp.quniform('eta', 0.005, 0.3, 0.005),\n",
    "        'seed': 0\n",
    "    }\n",
    "    \n",
    "    trials = Trials()\n",
    "    \n",
    "    best_hyperparams = fmin(fn = objective,\n",
    "                        space = space,\n",
    "                        algo = tpe.suggest,\n",
    "                        max_evals = 100,\n",
    "                        trials = trials)\n",
    "        \n",
    "    print(\"The best hyperparameters are : \",\"\\n\")\n",
    "    print(best_hyperparams)\n",
    "    return best_hyperparams"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "100%|██████████| 100/100 [38:54<00:00, 23.34s/trial, best loss: -0.9307125269082412]\n",
      "The best hyperparameters are :  \n",
      "\n",
      "{'colsample_bytree': 0.5538867630253574, 'gamma': 1.189016388208675, 'max_depth': 16.0, 'min_child_weight': 4.0, 'n_estimators': 350.0, 'reg_alpha': 0.0, 'reg_lambda': 0.15461796835519892}\n"
     ]
    }
   ],
   "source": [
    "best_hyperparams = tunne_together_XGBoost_classification(df_features, features, verbose=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "def XGBoost_classification_tunned_old(best_hyperparams, X_train=None, X_test=None, y_train=None, y_test=None):\n",
    "      if X_train is None:\n",
    "            X=df_features[features]  # Features\n",
    "            y=df_features['LABEL_code']  # Labels\n",
    "            #Split on train and test\n",
    "            X_train_a, X_test_a, y_train, y_test = train_test_split(X, y, test_size=0.30, stratify=y) # 70% training and 30% test\n",
    "            X_train = X_train_a[features]\n",
    "            X_test = X_test_a[features] \n",
    "      \n",
    "      model = XGBClassifier(\n",
    "            n_estimators = int(best_hyperparams['n_estimators']), max_depth = int(best_hyperparams['max_depth']), gamma = best_hyperparams['gamma'],\n",
    "            reg_alpha = int(best_hyperparams['reg_alpha']),min_child_weight=int(best_hyperparams['min_child_weight']),\n",
    "            colsample_bytree=int(best_hyperparams['colsample_bytree']),\n",
    "            # subsample=int(best_hyperparams['subsample']),\n",
    "            # eta=best_hyperparams['eta'],\n",
    "      )\n",
    "      model.fit(X_train, y_train)\n",
    "      y_pred = model.predict(X_test)\n",
    "      \n",
    "      print(classification_report(y_test, y_pred, target_names=classifications_array, digits=4))\n",
    "      matrix, percentage_matrix = get_confusion_matrix(y_test, y_pred)\n",
    "      plot_confusion_matrix(matrix, percentage_matrix, model=\"XGBoost\")\n",
    "      return model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "               precision    recall  f1-score   support\n",
      "\n",
      "        AUDIO     0.8312    0.6970    0.7582      1109\n",
      "     BROWSING     0.9209    0.9739    0.9467     14344\n",
      "         CHAT     0.7283    0.3116    0.4365       215\n",
      "FILE_TRANSFER     0.9876    0.9243    0.9549      1031\n",
      "         MAIL     0.9103    0.4797    0.6283       148\n",
      "          P2P     0.9723    0.9858    0.9790     17919\n",
      "        VIDEO     0.7015    0.3528    0.4695      1046\n",
      "         VOIP     0.5613    0.4075    0.4722       427\n",
      "\n",
      "     accuracy                         0.9393     36239\n",
      "    macro avg     0.8267    0.6416    0.7057     36239\n",
      " weighted avg     0.9337    0.9393    0.9334     36239\n",
      "\n"
     ]
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1500x500 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "model = XGBoost_classification_tunned_old(best_hyperparams, X_train, X_test, y_train, y_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "def while_XGBoost_classification_tunned_old(best_hyperparams, cycles=100):\n",
    "    X=df_features[features]  # Features\n",
    "    y=df_features['LABEL_code']  # Labels\n",
    "    best = 0\n",
    "    best_model = None\n",
    "    report = None\n",
    "    i = 0\n",
    "    print(f\"\\r{i}\", end=\"\")\n",
    "    for i in range(cycles):\n",
    "        print(f\"\\r{i}\", end=\"\", flush=True)\n",
    "        tmp_f1 = 0\n",
    "        tmp_str = \"\"\n",
    "        #Split on train and test\n",
    "        X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.3, stratify=y) # 70% training and 30% test\n",
    "        # sm = SMOTE(random_state=100)\n",
    "        # X_train, y_train = sm.fit_resample(X_train, y_train)\n",
    "        # X_test, y_test = sm.fit_resample(X_test, y_test)\n",
    "        \n",
    "        model = XGBClassifier(\n",
    "            n_estimators = int(best_hyperparams['n_estimators']), max_depth = int(best_hyperparams['max_depth']), gamma = best_hyperparams['gamma'],\n",
    "            reg_alpha = int(best_hyperparams['reg_alpha']),min_child_weight=int(best_hyperparams['min_child_weight']),\n",
    "            colsample_bytree=int(best_hyperparams['colsample_bytree']),\n",
    "            # subsample=int(best_hyperparams['subsample']),\n",
    "            # eta=best_hyperparams['eta'],\n",
    "        )\n",
    "        model.fit(X_train, y_train, ) # eval_set=evaluation, eval_metric=[\"auc\",\"error\",\"logloss\"], verbose=False\n",
    "        y_pred = model.predict(X_test)\n",
    "        \n",
    "        F1 = f1_score(y_test, y_pred, average='macro')\n",
    "        if F1 > best:   \n",
    "            best = F1\n",
    "            best_model = model\n",
    "            report = classification_report(y_test, y_pred, target_names=classifications_array, digits=4)\n",
    "        \n",
    "    print(\"\")\n",
    "    print(report)\n",
    "    return best_model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "9\n",
      "               precision    recall  f1-score   support\n",
      "\n",
      "        AUDIO     0.7990    0.7312    0.7636       919\n",
      "     BROWSING     0.9211    0.9753    0.9474     11978\n",
      "         CHAT     0.8000    0.2652    0.3983       181\n",
      "FILE_TRANSFER     0.9899    0.9147    0.9508       856\n",
      "         MAIL     0.9054    0.5360    0.6734       125\n",
      "          P2P     0.9709    0.9856    0.9782     14956\n",
      "        VIDEO     0.6787    0.3471    0.4593       870\n",
      "         VOIP     0.7791    0.3588    0.4913       354\n",
      "\n",
      "     accuracy                         0.9399     30239\n",
      "    macro avg     0.8555    0.6392    0.7078     30239\n",
      " weighted avg     0.9346    0.9399    0.9334     30239\n",
      "\n"
     ]
    }
   ],
   "source": [
    "best_model = while_XGBoost_classification_tunned_old(best_hyperparams, cycles=10)"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Evaluation of model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "               precision    recall  f1-score   support\n",
      "\n",
      "        AUDIO     0.7797    0.7013    0.7384       636\n",
      "     BROWSING     0.9167    0.9724    0.9437      7887\n",
      "         CHAT     0.7674    0.3000    0.4314       110\n",
      "FILE_TRANSFER     0.9928    0.9368    0.9639       585\n",
      "         MAIL     0.9459    0.4605    0.6195        76\n",
      "          P2P     0.9700    0.9854    0.9776      9875\n",
      "        VIDEO     0.6912    0.3356    0.4518       587\n",
      "         VOIP     0.7522    0.3484    0.4762       244\n",
      "\n",
      "     accuracy                         0.9372     20000\n",
      "    macro avg     0.8520    0.6300    0.7003     20000\n",
      " weighted avg     0.9315    0.9372    0.9303     20000\n",
      "\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1500x500 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "X_test=df_validation[features]  # Features\n",
    "y_test=df_validation['LABEL_code']  # Labels\n",
    "\n",
    "y_pred = best_model.predict(X_test)\n",
    "\n",
    "print(classification_report(y_test, y_pred, target_names=classifications_array, digits=4))\n",
    "\n",
    "matrix, percentage_matrix = get_confusion_matrix(y_test, y_pred)\n",
    "plot_confusion_matrix(matrix, percentage_matrix, model=\"XGBoost\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "report = classification_report(y_test, y_pred, target_names=classifications_array,digits=4)\n",
    "\n",
    "import csv\n",
    "\n",
    "problem = \"TOR-multiclass\"\n",
    "with open(\"feature_reduction_results.csv\", \"a\") as f:\n",
    "    writer = csv.writer(f)\n",
    "    report = classification_report(y_test, y_pred, target_names=classifications_array, digits=4)\n",
    "    tmp = report.split(\"weighted avg\")\n",
    "    tmp_2 = tmp[0].split(\"macro avg\")\n",
    "    accuracy = tmp_2[0].split(\"accuracy\")[1].split()[0]\n",
    "    _ = tmp_2[1].split()\n",
    "    m_precision = _[0]\n",
    "    m_recall = _[1]\n",
    "    m_f1 = _[2]\n",
    "    _ = tmp[1].split()\n",
    "    w_precision = _[0]\n",
    "    w_recall = _[1]\n",
    "    w_f1 = _[2]\n",
    "    writer.writerow([problem, \"-\", accuracy, m_precision, m_recall, m_f1, w_precision, w_recall, w_f1])"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Feature importance"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 600x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "feat_importances = pd.Series(best_model.feature_importances_, index = X_test.columns).sort_values(ascending = True)\n",
    "\n",
    "f_sf = feat_importances[statistics_features].sum()\n",
    "f_tf = feat_importances[time_features].sum()\n",
    "f_df = feat_importances[distribution_features].sum()\n",
    "f_ff = feat_importances[frequency_features].sum()\n",
    "f_bf = feat_importances[behavior_features].sum()\n",
    "\n",
    "fig, ax = plt.subplots(figsize=(6, 6), subplot_kw=dict(aspect=\"equal\"))\n",
    "data = [f_sf, f_tf, f_df, f_ff, f_bf]\n",
    "ingredients = [\"Statistical-based\", \"Time-based\", \"Distribution-based\",  \"Frequency-based\",  \"Behavior-based\"]\n",
    "def func(pct, allvals):\n",
    "    return \"{:.1f}%\".format(pct)\n",
    "wedges, texts, autotexts = ax.pie(data, autopct=lambda pct: func(pct, data),\n",
    "                                  textprops=dict(color=\"w\"))\n",
    "ax.legend(wedges, ingredients,\n",
    "          loc=\"center\",\n",
    "          bbox_to_anchor=(0.5, 0, 0, -0.05),\n",
    "          prop={'size': 12},\n",
    "          ncol=2)\n",
    "plt.setp(autotexts, size=12, weight=\"bold\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[0.3393622, 0.1046077, 0.043674424, 0.09366252, 0.36082417]"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1500x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(15,5))\n",
    "ax.bar(feat_importances.keys(), feat_importances.values)\n",
    "plt.xticks(rotation = 90)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "SPECTRAL_SPREAD      0.003138\n",
       "MAX_POWER_FREQ       0.003239\n",
       "SPECTRAL_ENERGY      0.003339\n",
       "MAX_POWER            0.003386\n",
       "SPECTRAL_KURTOSIS    0.003591\n",
       "                       ...   \n",
       "ENTROPY              0.033140\n",
       "SIG_SPACES           0.040076\n",
       "VAR                  0.070488\n",
       "VAL                  0.073811\n",
       "PERIODICITY          0.138732\n",
       "Length: 73, dtype: float32"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "feat_importances"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'SPECTRAL_SPREAD': 0.0031383163295686245,\n",
       " 'MAX_POWER_FREQ': 0.003239123383536935,\n",
       " 'SPECTRAL_ENERGY': 0.00333886849693954,\n",
       " 'MAX_POWER': 0.0033859622199088335,\n",
       " 'SPECTRAL_KURTOSIS': 0.0035912019666284323,\n",
       " 'HURST_EXPONENT': 0.003736891085281968,\n",
       " 'FISHER_PEARSON_g1_SKEWNESS': 0.003757789498195052,\n",
       " 'PERIODICITY_SCDF': 0.003886051010340452,\n",
       " 'MIN_POWER_FREQ': 0.003894655266776681,\n",
       " 'AREA_VALUES_DISTRIBUTION': 0.0040257517248392105,\n",
       " 'SPECTRAL_SLOPE': 0.004034205339848995,\n",
       " 'PEARSON_SK1_SKEWNESS': 0.004195309244096279,\n",
       " 'GALTON_SKEWNESS': 0.004312529228627682,\n",
       " 'SPECTRAL_BANDWIDTH': 0.0044175186194479465,\n",
       " 'PERCENT_BELOW_MEAN': 0.0044284095056355,\n",
       " 'MEAN': 0.004536438267678022,\n",
       " 'SPECTRAL_CREST': 0.004551375284790993,\n",
       " 'STDEV': 0.004678890109062195,\n",
       " 'NORMAL_DISTRIBUTION': 0.004913699813187122,\n",
       " 'P_BENFORD': 0.004956452175974846,\n",
       " 'MEAN_SCALED_TIME': 0.00503941485658288,\n",
       " 'Q3_SCALED_TIME': 0.005299307405948639,\n",
       " 'MIN_MINUS_MAX': 0.005731610115617514,\n",
       " 'MEAN_SCALED_DIFFTIMES': 0.005821323953568935,\n",
       " 'CNT_NZ_DISTRIBUTION': 0.00583398574963212,\n",
       " 'FISHER_PEARSON_G1_SKEWNESS': 0.005922316573560238,\n",
       " 'SPECTRAL_ENTROPY': 0.006107988301664591,\n",
       " 'SPECTRAL_CENTROID': 0.006244951859116554,\n",
       " 'ROOT_MEAN_SQUARE': 0.006258612964302301,\n",
       " 'COEFFICIENT_OF_VARIATION': 0.006312943063676357,\n",
       " 'SPECTRAL_SKEWNESS': 0.0064584240317344666,\n",
       " 'FISHER_MI_3_SKEWNESS': 0.006534573156386614,\n",
       " 'SPECTRAL_ROLLOFF': 0.006830087397247553,\n",
       " 'MEDIAN_DIFFTIMES': 0.007003821432590485,\n",
       " 'BURSTINESS': 0.007564891595393419,\n",
       " 'TIME_DISTRIBUTION': 0.007574311923235655,\n",
       " 'MEDIAN_SCALED_TIME': 0.007640380412340164,\n",
       " 'PERCENT_ABOVE_MEAN': 0.007757664658129215,\n",
       " 'CNT_DISTRIBUTION': 0.00856341514736414,\n",
       " 'SWITCHING_METRIC': 0.008731947280466557,\n",
       " 'MAX': 0.009119384922087193,\n",
       " 'KURTOSIS': 0.009776296094059944,\n",
       " 'BENFORD_LAW_PRESENTED': 0.00990390032529831,\n",
       " 'TIME': 0.009948302060365677,\n",
       " 'DURATION': 0.01048247143626213,\n",
       " 'Q1_SCALED_TIME': 0.010858815163373947,\n",
       " 'PEARSON_SK2_SKEWNESS': 0.01096290722489357,\n",
       " 'BYTES': 0.011240962892770767,\n",
       " 'MIN_POWER': 0.011295734904706478,\n",
       " 'MAX_DIFFTIMES': 0.012052536010742188,\n",
       " 'BYTES_REV': 0.012115351855754852,\n",
       " 'MIN': 0.012931478209793568,\n",
       " 'PACKETS': 0.013811332173645496,\n",
       " 'AVERAGE_DISPERSION': 0.014403474517166615,\n",
       " 'BIGGEST_CNT_1_SEC': 0.014507287181913853,\n",
       " 'PERCENT_DEVIATION': 0.015146546065807343,\n",
       " 'SCALED_ENTROPY': 0.015268619172275066,\n",
       " 'Q1': 0.016450190916657448,\n",
       " 'Q3': 0.016497906297445297,\n",
       " 'CNT_ZEROS': 0.017259802669286728,\n",
       " 'MIN_DIFFTIMES': 0.018329069018363953,\n",
       " 'SPECTRAL_FLUX': 0.019248059019446373,\n",
       " 'TRANSIENTS': 0.02035146951675415,\n",
       " 'PACKETS_REV': 0.020701467990875244,\n",
       " 'MODE': 0.020727967843413353,\n",
       " 'MEAN_DIFFTIMES': 0.0220805574208498,\n",
       " 'MEDIAN': 0.022456815466284752,\n",
       " 'DIRECTIONS': 0.031572867184877396,\n",
       " 'ENTROPY': 0.033140335232019424,\n",
       " 'SIG_SPACES': 0.040075674653053284,\n",
       " 'VAR': 0.07048830389976501,\n",
       " 'VAL': 0.07381105422973633,\n",
       " 'PERIODICITY': 0.13873174786567688}"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "feat_importances.to_dict()"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# FEATURE SELECTION"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [],
   "source": [
    "def perform_val(selected_features, cycles = 5, best_hyperparams=None):\n",
    "    if best_hyperparams is None:\n",
    "        best_hyperparams = tunne_together_XGBoost_classification(df_features.sample(25000), selected_features, verbose=False)\n",
    "    X_dos=df_features[selected_features]  # Features\n",
    "    y_dos=df_features['LABEL_code']  # Labels\n",
    "\n",
    "    best = 0\n",
    "    best_model = None\n",
    "    for i in range(0, cycles):    \n",
    "        X_train, X_test, y_train, y_test = train_test_split(X_dos, y_dos, test_size=0.30, stratify=y_dos) # 70% training and 30% test\n",
    "        model = XGBClassifier(\n",
    "            n_estimators = int(best_hyperparams['n_estimators']), max_depth = int(best_hyperparams['max_depth']), gamma = best_hyperparams['gamma'],\n",
    "            reg_alpha = int(best_hyperparams['reg_alpha']),min_child_weight=int(best_hyperparams['min_child_weight']),\n",
    "            colsample_bytree=int(best_hyperparams['colsample_bytree']),\n",
    "            )\n",
    "        model.fit(X_train, y_train)                \n",
    "        y_pred = model.predict(X_test)\n",
    "        F1 = f1_score(y_test, y_pred, average='macro')\n",
    "        if F1 > best:   \n",
    "            best = F1\n",
    "            best_model = model\n",
    "            \n",
    "    print(F1)\n",
    "\n",
    "    X_validation=df_validation[selected_features]  # Features\n",
    "    y_validation=df_validation['LABEL_code']  # Labels\n",
    "\n",
    "    y_pred = best_model.predict(X_validation)\n",
    "    \n",
    "    report = classification_report(y_validation,y_pred)\n",
    "    return report"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "100%|██████████| 100/100 [09:25<00:00,  5.66s/trial, best loss: -0.8731403544058607]\n",
      "The best hyperparameters are :  \n",
      "\n",
      "{'colsample_bytree': 0.6051096058633029, 'gamma': 2.2353897227777386, 'max_depth': 16.0, 'min_child_weight': 0.0, 'n_estimators': 200.0, 'reg_alpha': 0.0, 'reg_lambda': 0.6036309596894849}\n",
      "0.6198236464922198\n",
      "100%|██████████| 100/100 [07:54<00:00,  4.74s/trial, best loss: -0.8714482428742292]\n",
      "The best hyperparameters are :  \n",
      "\n",
      "{'colsample_bytree': 0.37537542513954464, 'gamma': 2.3712028821142708, 'max_depth': 12.0, 'min_child_weight': 10.0, 'n_estimators': 400.0, 'reg_alpha': 0.0, 'reg_lambda': 0.7472804860645826}\n",
      "0.6224697119925501\n",
      "100%|██████████| 100/100 [07:20<00:00,  4.41s/trial, best loss: -0.8787926543536856]\n",
      "The best hyperparameters are :  \n",
      "\n",
      "{'colsample_bytree': 0.42905474294262785, 'gamma': 1.5394958003322678, 'max_depth': 4.0, 'min_child_weight': 4.0, 'n_estimators': 400.0, 'reg_alpha': 0.0, 'reg_lambda': 0.9692474537432294}\n",
      "0.630208325690093\n",
      "100%|██████████| 100/100 [08:07<00:00,  4.88s/trial, best loss: -0.8748381860813333]\n",
      "The best hyperparameters are :  \n",
      "\n",
      "{'colsample_bytree': 0.5911307500177774, 'gamma': 2.487288702336408, 'max_depth': 28.0, 'min_child_weight': 6.0, 'n_estimators': 400.0, 'reg_alpha': 0.0, 'reg_lambda': 0.34871684292569927}\n",
      "0.6314469960178593\n",
      "100%|██████████| 100/100 [14:20<00:00,  8.61s/trial, best loss: -0.8908686472385919]\n",
      "The best hyperparameters are :  \n",
      "\n",
      "{'colsample_bytree': 0.31834516020853026, 'gamma': 1.1434945474632072, 'max_depth': 16.0, 'min_child_weight': 6.0, 'n_estimators': 450.0, 'reg_alpha': 0.0, 'reg_lambda': 0.7268322419789752}\n",
      "0.6707150560717902\n",
      "100%|██████████| 100/100 [07:59<00:00,  4.79s/trial, best loss: -0.8706945614949111]\n",
      "The best hyperparameters are :  \n",
      "\n",
      "{'colsample_bytree': 0.1019066334679215, 'gamma': 2.6697036575318487, 'max_depth': 8.0, 'min_child_weight': 0.0, 'n_estimators': 450.0, 'reg_alpha': 0.0, 'reg_lambda': 0.5713587107895544}\n",
      "0.6040656880660216\n",
      "100%|██████████| 100/100 [08:54<00:00,  5.35s/trial, best loss: -0.8631845164136671]\n",
      "The best hyperparameters are :  \n",
      "\n",
      "{'colsample_bytree': 0.20892489139803538, 'gamma': 1.9614402143044247, 'max_depth': 4.0, 'min_child_weight': 8.0, 'n_estimators': 300.0, 'reg_alpha': 0.0, 'reg_lambda': 0.028424392979519198}\n",
      "0.6136310636474485\n",
      "100%|██████████| 100/100 [07:52<00:00,  4.73s/trial, best loss: -0.875699060526895]\n",
      "The best hyperparameters are :  \n",
      "\n",
      "{'colsample_bytree': 0.8188909925345825, 'gamma': 3.200513590166334, 'max_depth': 4.0, 'min_child_weight': 16.0, 'n_estimators': 350.0, 'reg_alpha': 0.0, 'reg_lambda': 0.630365873205766}\n",
      "0.5876441337149675\n",
      "100%|██████████| 100/100 [08:32<00:00,  5.12s/trial, best loss: -0.8839963547560141]\n",
      "The best hyperparameters are :  \n",
      "\n",
      "{'colsample_bytree': 0.08680063344650782, 'gamma': 1.517274065121185, 'max_depth': 4.0, 'min_child_weight': 0.0, 'n_estimators': 450.0, 'reg_alpha': 0.0, 'reg_lambda': 0.5594499477679974}\n",
      "0.6207861459574355\n",
      "100%|██████████| 100/100 [08:24<00:00,  5.04s/trial, best loss: -0.8753009418113713]\n",
      "The best hyperparameters are :  \n",
      "\n",
      "{'colsample_bytree': 0.6368711681132752, 'gamma': 1.0401353679596674, 'max_depth': 12.0, 'min_child_weight': 4.0, 'n_estimators': 500.0, 'reg_alpha': 0.0, 'reg_lambda': 0.6452110585866571}\n",
      "0.6555660389253466\n"
     ]
    }
   ],
   "source": [
    "import FEATURE_REDUCTED as FR\n",
    "REPORTS = []\n",
    "\n",
    "\n",
    "report = perform_val(FR.botnet_best_features)\n",
    "REPORTS.append(report)\n",
    "report = perform_val(FR.doh_best_features)\n",
    "REPORTS.append(report)\n",
    "report = perform_val(FR.dos_best_features)\n",
    "REPORTS.append(report)\n",
    "report = perform_val(FR.dns_malware_features)\n",
    "REPORTS.append(report)\n",
    "report = perform_val(FR.tor_features)\n",
    "REPORTS.append(report)\n",
    "report = perform_val(FR.vpn_features)\n",
    "REPORTS.append(report)\n",
    "report = perform_val(FR.all_best_features)\n",
    "REPORTS.append(report)\n",
    "report = perform_val(FR.combo_features)\n",
    "REPORTS.append(report)\n",
    "report = perform_val(FR.combo_2_features)\n",
    "REPORTS.append(report)\n",
    "report = perform_val(FR.crypto_features)\n",
    "REPORTS.append(report)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [],
   "source": [
    "problem = \"TOR-multiclass\"\n",
    "with open(\"feature_reduction_results.csv\", \"a\") as f:\n",
    "    writer = csv.writer(f)\n",
    "    for report, f_set in zip(REPORTS, FR.FEATURE_SETS):\n",
    "        tmp = report.split(\"weighted avg\")\n",
    "        tmp_2 = tmp[0].split(\"macro avg\")\n",
    "        accuracy = tmp_2[0].split(\"accuracy\")[1].split()[0]\n",
    "        _ = tmp_2[1].split()\n",
    "        m_precision = _[0]\n",
    "        m_recall = _[1]\n",
    "        m_f1 = _[2]\n",
    "        _ = tmp[1].split()\n",
    "        w_precision = _[0]\n",
    "        w_recall = _[1]\n",
    "        w_f1 = _[2]\n",
    "        writer.writerow([problem, f_set, accuracy, m_precision, m_recall, m_f1, w_precision, w_recall, w_f1])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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