incs870_team4.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "provenance": [],
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/MeenaRuwandi/INCS_870_Project_IDSforMinorAttacks/blob/siwon/incs870_team4.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "!pip install imbalanced-learn\n",
        "!pip install scikit-learn"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "kAonk6lUz5UI",
        "outputId": "6703e97d-4f1f-4bc8-b279-e77c7c5097bc"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Requirement already satisfied: imbalanced-learn in /usr/local/lib/python3.10/dist-packages (0.12.3)\n",
            "Requirement already satisfied: numpy>=1.17.3 in /usr/local/lib/python3.10/dist-packages (from imbalanced-learn) (1.26.4)\n",
            "Requirement already satisfied: scipy>=1.5.0 in /usr/local/lib/python3.10/dist-packages (from imbalanced-learn) (1.13.1)\n",
            "Requirement already satisfied: scikit-learn>=1.0.2 in /usr/local/lib/python3.10/dist-packages (from imbalanced-learn) (1.5.2)\n",
            "Requirement already satisfied: joblib>=1.1.1 in /usr/local/lib/python3.10/dist-packages (from imbalanced-learn) (1.4.2)\n",
            "Requirement already satisfied: threadpoolctl>=2.0.0 in /usr/local/lib/python3.10/dist-packages (from imbalanced-learn) (3.5.0)\n",
            "Requirement already satisfied: scikit-learn in /usr/local/lib/python3.10/dist-packages (1.5.2)\n",
            "Requirement already satisfied: numpy>=1.19.5 in /usr/local/lib/python3.10/dist-packages (from scikit-learn) (1.26.4)\n",
            "Requirement already satisfied: scipy>=1.6.0 in /usr/local/lib/python3.10/dist-packages (from scikit-learn) (1.13.1)\n",
            "Requirement already satisfied: joblib>=1.2.0 in /usr/local/lib/python3.10/dist-packages (from scikit-learn) (1.4.2)\n",
            "Requirement already satisfied: threadpoolctl>=3.1.0 in /usr/local/lib/python3.10/dist-packages (from scikit-learn) (3.5.0)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "xJzGzg0FzrC0",
        "outputId": "3838576d-7633-41c0-d420-86cd3428475c"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Requirement already satisfied: gdown in /usr/local/lib/python3.10/dist-packages (5.2.0)\n",
            "Requirement already satisfied: beautifulsoup4 in /usr/local/lib/python3.10/dist-packages (from gdown) (4.12.3)\n",
            "Requirement already satisfied: filelock in /usr/local/lib/python3.10/dist-packages (from gdown) (3.16.1)\n",
            "Requirement already satisfied: requests[socks] in /usr/local/lib/python3.10/dist-packages (from gdown) (2.32.3)\n",
            "Requirement already satisfied: tqdm in /usr/local/lib/python3.10/dist-packages (from gdown) (4.66.5)\n",
            "Requirement already satisfied: soupsieve>1.2 in /usr/local/lib/python3.10/dist-packages (from beautifulsoup4->gdown) (2.6)\n",
            "Requirement already satisfied: charset-normalizer<4,>=2 in /usr/local/lib/python3.10/dist-packages (from requests[socks]->gdown) (3.3.2)\n",
            "Requirement already satisfied: idna<4,>=2.5 in /usr/local/lib/python3.10/dist-packages (from requests[socks]->gdown) (3.10)\n",
            "Requirement already satisfied: urllib3<3,>=1.21.1 in /usr/local/lib/python3.10/dist-packages (from requests[socks]->gdown) (2.2.3)\n",
            "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.10/dist-packages (from requests[socks]->gdown) (2024.8.30)\n",
            "Requirement already satisfied: PySocks!=1.5.7,>=1.5.6 in /usr/local/lib/python3.10/dist-packages (from requests[socks]->gdown) (1.7.1)\n"
          ]
        }
      ],
      "source": [
        "!pip install gdown\n",
        "import gdown"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Required Libraries\n",
        "import pandas as pd\n",
        "from sklearn.model_selection import train_test_split\n",
        "from sklearn.preprocessing import StandardScaler\n",
        "from imblearn.over_sampling import SMOTE\n",
        "from sklearn.ensemble import RandomForestClassifier\n",
        "from sklearn.metrics import classification_report, confusion_matrix"
      ],
      "metadata": {
        "id": "G2mRgdV89K2S"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "file_ids = [\n",
        "    '1zOeCqtGZjAj_nSLe3W5MH5pDQM28bPde',  # Replace with actual file ID\n",
        "    '1fagr2rKW8EN-Psc5UlD9BFfa0rRRF6i3',  # Replace with actual file ID\n",
        "    '1WL00LFkCA2ylV8_8c6jm52bnEhGLcKsq',   # Replace with actual file ID\n",
        "    '1xr_QBU3Ab42nW1ELl0NUydx4Rbx60TVR',\n",
        "    '1MpqHsC5wQSu9CxlhJimz25EVcYubSMhu',\n",
        "    '18mKfJHXinmfwPpaYNU2D6xHwq4dQuEuL',\n",
        "    '1h1lMHytamf4Kc66NfAfMfBzDbmwM5Ub5',\n",
        "    '11__JhC64_D4ezxjF8d0dPNRDJF-TY6Pq'\n",
        "]\n",
        "\n",
        "\n",
        "# Download each file\n",
        "for i, file_id in enumerate(file_ids):\n",
        "    url = f'https://drive.google.com/uc?id={file_id}'\n",
        "    gdown.download(url, f'dataset_{i + 1}.csv', quiet=False)  # Saves as dataset_1.csv, dataset_2.csv, etc."
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "yQuMhkmd0NNe",
        "outputId": "e939f3b9-6158-4902-d1da-3a02ec83fdff"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "Downloading...\n",
            "From (original): https://drive.google.com/uc?id=1zOeCqtGZjAj_nSLe3W5MH5pDQM28bPde\n",
            "From (redirected): https://drive.google.com/uc?id=1zOeCqtGZjAj_nSLe3W5MH5pDQM28bPde&confirm=t&uuid=89026891-5b2d-4782-b0b2-1265b224d305\n",
            "To: /content/dataset_1.csv\n",
            "100%|██████████| 225M/225M [00:03<00:00, 66.7MB/s]\n",
            "Downloading...\n",
            "From (original): https://drive.google.com/uc?id=1fagr2rKW8EN-Psc5UlD9BFfa0rRRF6i3\n",
            "From (redirected): https://drive.google.com/uc?id=1fagr2rKW8EN-Psc5UlD9BFfa0rRRF6i3&confirm=t&uuid=4a6a1855-52df-49ee-87d2-f9bd9fee12d6\n",
            "To: /content/dataset_2.csv\n",
            "100%|██████████| 135M/135M [00:02<00:00, 50.9MB/s]\n",
            "Downloading...\n",
            "From: https://drive.google.com/uc?id=1WL00LFkCA2ylV8_8c6jm52bnEhGLcKsq\n",
            "To: /content/dataset_3.csv\n",
            "100%|██████████| 52.0M/52.0M [00:00<00:00, 149MB/s]\n",
            "Downloading...\n",
            "From: https://drive.google.com/uc?id=1xr_QBU3Ab42nW1ELl0NUydx4Rbx60TVR\n",
            "To: /content/dataset_4.csv\n",
            "100%|██████████| 83.1M/83.1M [00:00<00:00, 166MB/s]\n",
            "Downloading...\n",
            "From (original): https://drive.google.com/uc?id=1MpqHsC5wQSu9CxlhJimz25EVcYubSMhu\n",
            "From (redirected): https://drive.google.com/uc?id=1MpqHsC5wQSu9CxlhJimz25EVcYubSMhu&confirm=t&uuid=fa439431-74e8-49a8-843a-70f764837f1a\n",
            "To: /content/dataset_5.csv\n",
            "100%|██████████| 177M/177M [00:02<00:00, 69.7MB/s]\n",
            "Downloading...\n",
            "From: https://drive.google.com/uc?id=18mKfJHXinmfwPpaYNU2D6xHwq4dQuEuL\n",
            "To: /content/dataset_6.csv\n",
            "100%|██████████| 58.3M/58.3M [00:00<00:00, 144MB/s]\n",
            "Downloading...\n",
            "From: https://drive.google.com/uc?id=1h1lMHytamf4Kc66NfAfMfBzDbmwM5Ub5\n",
            "To: /content/dataset_7.csv\n",
            "100%|██████████| 76.9M/76.9M [00:00<00:00, 187MB/s]\n",
            "Downloading...\n",
            "From: https://drive.google.com/uc?id=11__JhC64_D4ezxjF8d0dPNRDJF-TY6Pq\n",
            "To: /content/dataset_8.csv\n",
            "100%|██████████| 77.1M/77.1M [00:01<00:00, 58.2MB/s]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "dataset_paths = [\n",
        "    '/content/dataset_1.csv','/content/dataset_2.csv','/content/dataset_3.csv','/content/dataset_4.csv',\n",
        "    '/content/dataset_5.csv','/content/dataset_6.csv','/content/dataset_7.csv','/content/dataset_8.csv',\n",
        "]\n",
        "\n",
        "# Make the data frame\n",
        "dataframes = [pd.read_csv(path) for path in dataset_paths]\n",
        "\n",
        "# Combine all datasets into one dataframe\n",
        "combined_dataset = pd.concat(dataframes, ignore_index=True)"
      ],
      "metadata": {
        "id": "Z4B6Sgje9cA8"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "combined_dataset.describe()"
      ],
      "metadata": {
        "id": "M4JSokVCATPY",
        "outputId": "9466a774-b597-4fe0-f463-12e9a1dcea5c",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 453
        }
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/pandas/core/nanops.py:1010: RuntimeWarning: invalid value encountered in subtract\n",
            "  sqr = _ensure_numeric((avg - values) ** 2)\n",
            "/usr/local/lib/python3.10/dist-packages/pandas/core/nanops.py:1010: RuntimeWarning: invalid value encountered in subtract\n",
            "  sqr = _ensure_numeric((avg - values) ** 2)\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "        Destination Port   Flow Duration   Total Fwd Packets  \\\n",
              "count       2.830743e+06    2.830743e+06        2.830743e+06   \n",
              "mean        8.071483e+03    1.478566e+07        9.361160e+00   \n",
              "std         1.828363e+04    3.365374e+07        7.496728e+02   \n",
              "min         0.000000e+00   -1.300000e+01        1.000000e+00   \n",
              "25%         5.300000e+01    1.550000e+02        2.000000e+00   \n",
              "50%         8.000000e+01    3.131600e+04        2.000000e+00   \n",
              "75%         4.430000e+02    3.204828e+06        5.000000e+00   \n",
              "max         6.553500e+04    1.200000e+08        2.197590e+05   \n",
              "\n",
              "        Total Backward Packets  Total Length of Fwd Packets  \\\n",
              "count             2.830743e+06                 2.830743e+06   \n",
              "mean              1.039377e+01                 5.493024e+02   \n",
              "std               9.973883e+02                 9.993589e+03   \n",
              "min               0.000000e+00                 0.000000e+00   \n",
              "25%               1.000000e+00                 1.200000e+01   \n",
              "50%               2.000000e+00                 6.200000e+01   \n",
              "75%               4.000000e+00                 1.870000e+02   \n",
              "max               2.919220e+05                 1.290000e+07   \n",
              "\n",
              "        Total Length of Bwd Packets   Fwd Packet Length Max  \\\n",
              "count                  2.830743e+06            2.830743e+06   \n",
              "mean                   1.616264e+04            2.075999e+02   \n",
              "std                    2.263088e+06            7.171848e+02   \n",
              "min                    0.000000e+00            0.000000e+00   \n",
              "25%                    0.000000e+00            6.000000e+00   \n",
              "50%                    1.230000e+02            3.700000e+01   \n",
              "75%                    4.820000e+02            8.100000e+01   \n",
              "max                    6.554530e+08            2.482000e+04   \n",
              "\n",
              "        Fwd Packet Length Min   Fwd Packet Length Mean  \\\n",
              "count            2.830743e+06             2.830743e+06   \n",
              "mean             1.871366e+01             5.820194e+01   \n",
              "std              6.033935e+01             1.860912e+02   \n",
              "min              0.000000e+00             0.000000e+00   \n",
              "25%              0.000000e+00             6.000000e+00   \n",
              "50%              2.000000e+00             3.400000e+01   \n",
              "75%              3.600000e+01             5.000000e+01   \n",
              "max              2.325000e+03             5.940857e+03   \n",
              "\n",
              "        Fwd Packet Length Std  ...   act_data_pkt_fwd   min_seg_size_forward  \\\n",
              "count            2.830743e+06  ...       2.830743e+06           2.830743e+06   \n",
              "mean             6.891013e+01  ...       5.418218e+00          -2.741688e+03   \n",
              "std              2.811871e+02  ...       6.364257e+02           1.084989e+06   \n",
              "min              0.000000e+00  ...       0.000000e+00          -5.368707e+08   \n",
              "25%              0.000000e+00  ...       0.000000e+00           2.000000e+01   \n",
              "50%              0.000000e+00  ...       1.000000e+00           2.400000e+01   \n",
              "75%              2.616295e+01  ...       2.000000e+00           3.200000e+01   \n",
              "max              7.125597e+03  ...       2.135570e+05           1.380000e+02   \n",
              "\n",
              "        Active Mean    Active Std    Active Max    Active Min     Idle Mean  \\\n",
              "count  2.830743e+06  2.830743e+06  2.830743e+06  2.830743e+06  2.830743e+06   \n",
              "mean   8.155132e+04  4.113412e+04  1.531825e+05  5.829582e+04  8.316037e+06   \n",
              "std    6.485999e+05  3.933815e+05  1.025825e+06  5.770923e+05  2.363008e+07   \n",
              "min    0.000000e+00  0.000000e+00  0.000000e+00  0.000000e+00  0.000000e+00   \n",
              "25%    0.000000e+00  0.000000e+00  0.000000e+00  0.000000e+00  0.000000e+00   \n",
              "50%    0.000000e+00  0.000000e+00  0.000000e+00  0.000000e+00  0.000000e+00   \n",
              "75%    0.000000e+00  0.000000e+00  0.000000e+00  0.000000e+00  0.000000e+00   \n",
              "max    1.100000e+08  7.420000e+07  1.100000e+08  1.100000e+08  1.200000e+08   \n",
              "\n",
              "           Idle Std      Idle Max      Idle Min  \n",
              "count  2.830743e+06  2.830743e+06  2.830743e+06  \n",
              "mean   5.038439e+05  8.695752e+06  7.920031e+06  \n",
              "std    4.602984e+06  2.436689e+07  2.336342e+07  \n",
              "min    0.000000e+00  0.000000e+00  0.000000e+00  \n",
              "25%    0.000000e+00  0.000000e+00  0.000000e+00  \n",
              "50%    0.000000e+00  0.000000e+00  0.000000e+00  \n",
              "75%    0.000000e+00  0.000000e+00  0.000000e+00  \n",
              "max    7.690000e+07  1.200000e+08  1.200000e+08  \n",
              "\n",
              "[8 rows x 78 columns]"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-d5c2fedf-5784-4a2b-aa88-21fd8fdccf29\" class=\"colab-df-container\">\n",
              "    <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>Destination Port</th>\n",
              "      <th>Flow Duration</th>\n",
              "      <th>Total Fwd Packets</th>\n",
              "      <th>Total Backward Packets</th>\n",
              "      <th>Total Length of Fwd Packets</th>\n",
              "      <th>Total Length of Bwd Packets</th>\n",
              "      <th>Fwd Packet Length Max</th>\n",
              "      <th>Fwd Packet Length Min</th>\n",
              "      <th>Fwd Packet Length Mean</th>\n",
              "      <th>Fwd Packet Length Std</th>\n",
              "      <th>...</th>\n",
              "      <th>act_data_pkt_fwd</th>\n",
              "      <th>min_seg_size_forward</th>\n",
              "      <th>Active Mean</th>\n",
              "      <th>Active Std</th>\n",
              "      <th>Active Max</th>\n",
              "      <th>Active Min</th>\n",
              "      <th>Idle Mean</th>\n",
              "      <th>Idle Std</th>\n",
              "      <th>Idle Max</th>\n",
              "      <th>Idle Min</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>count</th>\n",
              "      <td>2.830743e+06</td>\n",
              "      <td>2.830743e+06</td>\n",
              "      <td>2.830743e+06</td>\n",
              "      <td>2.830743e+06</td>\n",
              "      <td>2.830743e+06</td>\n",
              "      <td>2.830743e+06</td>\n",
              "      <td>2.830743e+06</td>\n",
              "      <td>2.830743e+06</td>\n",
              "      <td>2.830743e+06</td>\n",
              "      <td>2.830743e+06</td>\n",
              "      <td>...</td>\n",
              "      <td>2.830743e+06</td>\n",
              "      <td>2.830743e+06</td>\n",
              "      <td>2.830743e+06</td>\n",
              "      <td>2.830743e+06</td>\n",
              "      <td>2.830743e+06</td>\n",
              "      <td>2.830743e+06</td>\n",
              "      <td>2.830743e+06</td>\n",
              "      <td>2.830743e+06</td>\n",
              "      <td>2.830743e+06</td>\n",
              "      <td>2.830743e+06</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>mean</th>\n",
              "      <td>8.071483e+03</td>\n",
              "      <td>1.478566e+07</td>\n",
              "      <td>9.361160e+00</td>\n",
              "      <td>1.039377e+01</td>\n",
              "      <td>5.493024e+02</td>\n",
              "      <td>1.616264e+04</td>\n",
              "      <td>2.075999e+02</td>\n",
              "      <td>1.871366e+01</td>\n",
              "      <td>5.820194e+01</td>\n",
              "      <td>6.891013e+01</td>\n",
              "      <td>...</td>\n",
              "      <td>5.418218e+00</td>\n",
              "      <td>-2.741688e+03</td>\n",
              "      <td>8.155132e+04</td>\n",
              "      <td>4.113412e+04</td>\n",
              "      <td>1.531825e+05</td>\n",
              "      <td>5.829582e+04</td>\n",
              "      <td>8.316037e+06</td>\n",
              "      <td>5.038439e+05</td>\n",
              "      <td>8.695752e+06</td>\n",
              "      <td>7.920031e+06</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>std</th>\n",
              "      <td>1.828363e+04</td>\n",
              "      <td>3.365374e+07</td>\n",
              "      <td>7.496728e+02</td>\n",
              "      <td>9.973883e+02</td>\n",
              "      <td>9.993589e+03</td>\n",
              "      <td>2.263088e+06</td>\n",
              "      <td>7.171848e+02</td>\n",
              "      <td>6.033935e+01</td>\n",
              "      <td>1.860912e+02</td>\n",
              "      <td>2.811871e+02</td>\n",
              "      <td>...</td>\n",
              "      <td>6.364257e+02</td>\n",
              "      <td>1.084989e+06</td>\n",
              "      <td>6.485999e+05</td>\n",
              "      <td>3.933815e+05</td>\n",
              "      <td>1.025825e+06</td>\n",
              "      <td>5.770923e+05</td>\n",
              "      <td>2.363008e+07</td>\n",
              "      <td>4.602984e+06</td>\n",
              "      <td>2.436689e+07</td>\n",
              "      <td>2.336342e+07</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>min</th>\n",
              "      <td>0.000000e+00</td>\n",
              "      <td>-1.300000e+01</td>\n",
              "      <td>1.000000e+00</td>\n",
              "      <td>0.000000e+00</td>\n",
              "      <td>0.000000e+00</td>\n",
              "      <td>0.000000e+00</td>\n",
              "      <td>0.000000e+00</td>\n",
              "      <td>0.000000e+00</td>\n",
              "      <td>0.000000e+00</td>\n",
              "      <td>0.000000e+00</td>\n",
              "      <td>...</td>\n",
              "      <td>0.000000e+00</td>\n",
              "      <td>-5.368707e+08</td>\n",
              "      <td>0.000000e+00</td>\n",
              "      <td>0.000000e+00</td>\n",
              "      <td>0.000000e+00</td>\n",
              "      <td>0.000000e+00</td>\n",
              "      <td>0.000000e+00</td>\n",
              "      <td>0.000000e+00</td>\n",
              "      <td>0.000000e+00</td>\n",
              "      <td>0.000000e+00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25%</th>\n",
              "      <td>5.300000e+01</td>\n",
              "      <td>1.550000e+02</td>\n",
              "      <td>2.000000e+00</td>\n",
              "      <td>1.000000e+00</td>\n",
              "      <td>1.200000e+01</td>\n",
              "      <td>0.000000e+00</td>\n",
              "      <td>6.000000e+00</td>\n",
              "      <td>0.000000e+00</td>\n",
              "      <td>6.000000e+00</td>\n",
              "      <td>0.000000e+00</td>\n",
              "      <td>...</td>\n",
              "      <td>0.000000e+00</td>\n",
              "      <td>2.000000e+01</td>\n",
              "      <td>0.000000e+00</td>\n",
              "      <td>0.000000e+00</td>\n",
              "      <td>0.000000e+00</td>\n",
              "      <td>0.000000e+00</td>\n",
              "      <td>0.000000e+00</td>\n",
              "      <td>0.000000e+00</td>\n",
              "      <td>0.000000e+00</td>\n",
              "      <td>0.000000e+00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>50%</th>\n",
              "      <td>8.000000e+01</td>\n",
              "      <td>3.131600e+04</td>\n",
              "      <td>2.000000e+00</td>\n",
              "      <td>2.000000e+00</td>\n",
              "      <td>6.200000e+01</td>\n",
              "      <td>1.230000e+02</td>\n",
              "      <td>3.700000e+01</td>\n",
              "      <td>2.000000e+00</td>\n",
              "      <td>3.400000e+01</td>\n",
              "      <td>0.000000e+00</td>\n",
              "      <td>...</td>\n",
              "      <td>1.000000e+00</td>\n",
              "      <td>2.400000e+01</td>\n",
              "      <td>0.000000e+00</td>\n",
              "      <td>0.000000e+00</td>\n",
              "      <td>0.000000e+00</td>\n",
              "      <td>0.000000e+00</td>\n",
              "      <td>0.000000e+00</td>\n",
              "      <td>0.000000e+00</td>\n",
              "      <td>0.000000e+00</td>\n",
              "      <td>0.000000e+00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>75%</th>\n",
              "      <td>4.430000e+02</td>\n",
              "      <td>3.204828e+06</td>\n",
              "      <td>5.000000e+00</td>\n",
              "      <td>4.000000e+00</td>\n",
              "      <td>1.870000e+02</td>\n",
              "      <td>4.820000e+02</td>\n",
              "      <td>8.100000e+01</td>\n",
              "      <td>3.600000e+01</td>\n",
              "      <td>5.000000e+01</td>\n",
              "      <td>2.616295e+01</td>\n",
              "      <td>...</td>\n",
              "      <td>2.000000e+00</td>\n",
              "      <td>3.200000e+01</td>\n",
              "      <td>0.000000e+00</td>\n",
              "      <td>0.000000e+00</td>\n",
              "      <td>0.000000e+00</td>\n",
              "      <td>0.000000e+00</td>\n",
              "      <td>0.000000e+00</td>\n",
              "      <td>0.000000e+00</td>\n",
              "      <td>0.000000e+00</td>\n",
              "      <td>0.000000e+00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>max</th>\n",
              "      <td>6.553500e+04</td>\n",
              "      <td>1.200000e+08</td>\n",
              "      <td>2.197590e+05</td>\n",
              "      <td>2.919220e+05</td>\n",
              "      <td>1.290000e+07</td>\n",
              "      <td>6.554530e+08</td>\n",
              "      <td>2.482000e+04</td>\n",
              "      <td>2.325000e+03</td>\n",
              "      <td>5.940857e+03</td>\n",
              "      <td>7.125597e+03</td>\n",
              "      <td>...</td>\n",
              "      <td>2.135570e+05</td>\n",
              "      <td>1.380000e+02</td>\n",
              "      <td>1.100000e+08</td>\n",
              "      <td>7.420000e+07</td>\n",
              "      <td>1.100000e+08</td>\n",
              "      <td>1.100000e+08</td>\n",
              "      <td>1.200000e+08</td>\n",
              "      <td>7.690000e+07</td>\n",
              "      <td>1.200000e+08</td>\n",
              "      <td>1.200000e+08</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>8 rows × 78 columns</p>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-d5c2fedf-5784-4a2b-aa88-21fd8fdccf29')\"\n",
              "            title=\"Convert this dataframe to an interactive table.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n",
              "    <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n",
              "  </svg>\n",
              "    </button>\n",
              "\n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-d5c2fedf-5784-4a2b-aa88-21fd8fdccf29 button.colab-df-convert');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      async function convertToInteractive(key) {\n",
              "        const element = document.querySelector('#df-d5c2fedf-5784-4a2b-aa88-21fd8fdccf29');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
              "        const docLink = document.createElement('div');\n",
              "        docLink.innerHTML = docLinkHtml;\n",
              "        element.appendChild(docLink);\n",
              "      }\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "\n",
              "<div id=\"df-335db29d-78cf-4ab8-bbcb-4da615945e9f\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-335db29d-78cf-4ab8-bbcb-4da615945e9f')\"\n",
              "            title=\"Suggest charts\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "     width=\"24px\">\n",
              "    <g>\n",
              "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-335db29d-78cf-4ab8-bbcb-4da615945e9f button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe"
            }
          },
          "metadata": {},
          "execution_count": 10
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "combined_dataset.shape"
      ],
      "metadata": {
        "id": "d3t3Uy7JAhj1",
        "outputId": "3ec8ef07-cc25-40df-c85c-754afe9a4a32",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(2830743, 79)"
            ]
          },
          "metadata": {},
          "execution_count": 12
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Pre processing\n",
        "x = combined_dataset.drop(columns=[' Label'])\n",
        "y = combined_dataset[' Label']\n",
        "# Handle missing values\n",
        "x.fillna(x.mean(), inplace=True)\n",
        "\n",
        "# Get 'Label' column that indicates attack types\n",
        "class_distribution = combined_dataset[' Label'].value_counts()\n",
        "print(class_distribution)"
      ],
      "metadata": {
        "id": "y7Zvt-PyBKnz",
        "outputId": "05506663-d7d1-47cf-8076-10da0a080dce",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            " Label\n",
            "BENIGN                        2273097\n",
            "DoS Hulk                       231073\n",
            "PortScan                       158930\n",
            "DDoS                           128027\n",
            "DoS GoldenEye                   10293\n",
            "FTP-Patator                      7938\n",
            "SSH-Patator                      5897\n",
            "DoS slowloris                    5796\n",
            "DoS Slowhttptest                 5499\n",
            "Bot                              1966\n",
            "Web Attack � Brute Force         1507\n",
            "Web Attack � XSS                  652\n",
            "Infiltration                       36\n",
            "Web Attack � Sql Injection         21\n",
            "Heartbleed                         11\n",
            "Name: count, dtype: int64\n"
          ]
        }
      ]
    }
  ]
}