convert_original_datasets/Convert for Device 8.ipynb

{"nbformat":4,"nbformat_minor":0,"metadata":{"colab":{"name":"Convert for Device 8.ipynb","provenance":[],"toc_visible":true,"authorship_tag":"ABX9TyN1cP+JT67/czOhZmrYzugQ"},"kernelspec":{"name":"python3","display_name":"Python 3"},"language_info":{"name":"python"}},"cells":[{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"vhML_9mQeosl","executionInfo":{"status":"ok","timestamp":1625203433892,"user_tz":-600,"elapsed":23107,"user":{"displayName":"Jane ZOU","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GhovXuga2ucGkqSP_krLzx1k4yHH4hCC5bJTF0L=s64","userId":"02928433389786515403"}},"outputId":"79ca5efd-72d5-4c6c-a098-9b7ba29b945c"},"source":["from google.colab import drive\n","drive.mount('/content/drive')"],"execution_count":1,"outputs":[{"output_type":"stream","text":["Mounted at /content/drive\n"],"name":"stdout"}]},{"cell_type":"code","metadata":{"id":"QKdnoUL3lGgk","executionInfo":{"status":"ok","timestamp":1625203434574,"user_tz":-600,"elapsed":689,"user":{"displayName":"Jane ZOU","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GhovXuga2ucGkqSP_krLzx1k4yHH4hCC5bJTF0L=s64","userId":"02928433389786515403"}}},"source":["import pandas as pd\n","import numpy as np\n","import matplotlib.pyplot as plt\n","from collections import Counter\n","from scipy import stats"],"execution_count":2,"outputs":[]},{"cell_type":"markdown","metadata":{"id":"Caxxoby4oxbP"},"source":["# Load Datasets"]},{"cell_type":"code","metadata":{"id":"zDZ1WaK0lGZb","executionInfo":{"status":"ok","timestamp":1625203467205,"user_tz":-600,"elapsed":32637,"user":{"displayName":"Jane ZOU","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GhovXuga2ucGkqSP_krLzx1k4yHH4hCC5bJTF0L=s64","userId":"02928433389786515403"}}},"source":["# IoT Device #2 --> device_2_Ecobee_Thermostat\n","benign = pd.read_csv('/content/drive/MyDrive/5703 CP/Datasets/8.benign.csv') \n","benign.shape\n","\n","# Botnet --> Mirai\n","# Attack --> Scan volnerable devices / Ack flooding / Syn flooding / UDP flooding / UDPplain\n","\n","m_scan = pd.read_csv('/content/drive/MyDrive/5703 CP/Datasets/8.mirai.scan.csv')\n","m_ack = pd.read_csv('/content/drive/MyDrive/5703 CP/Datasets/8.mirai.ack.csv')\n","m_syn = pd.read_csv('/content/drive/MyDrive/5703 CP/Datasets/8.mirai.syn.csv')\n","m_udp = pd.read_csv('/content/drive/MyDrive/5703 CP/Datasets/8.mirai.udp.csv')\n","m_udpplain = pd.read_csv('/content/drive/MyDrive/5703 CP/Datasets/8.mirai.udpplain.csv')\n","\n","#Botnet --> Gafgyt (BASHLITE)\n","#Attack --> Scan vulnerable devices / Sending spam / UDP flooding / TCP flooding / Sending spam & opening connection\n","g_scan = pd.read_csv('/content/drive/MyDrive/5703 CP/Datasets/8.gafgyt.scan.csv')\n","g_junk = pd.read_csv('/content/drive/MyDrive/5703 CP/Datasets/8.gafgyt.junk.csv')\n","g_udp = pd.read_csv('/content/drive/MyDrive/5703 CP/Datasets/8.gafgyt.udp.csv')\n","g_tcp = pd.read_csv('/content/drive/MyDrive/5703 CP/Datasets/8.gafgyt.tcp.csv')\n","g_combo = pd.read_csv('/content/drive/MyDrive/5703 CP/Datasets/8.gafgyt.combo.csv')"],"execution_count":3,"outputs":[]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"QxlE1MfhorlX","executionInfo":{"status":"ok","timestamp":1625203467232,"user_tz":-600,"elapsed":81,"user":{"displayName":"Jane ZOU","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GhovXuga2ucGkqSP_krLzx1k4yHH4hCC5bJTF0L=s64","userId":"02928433389786515403"}},"outputId":"fbc78b3b-fcec-465a-f291-6907c01d20cb"},"source":["print(m_scan.shape)\n","print(m_ack.shape)\n","print(m_syn.shape)\n","print(m_udp.shape)\n","print(m_udpplain.shape)\n","print(g_combo.shape)\n","print(g_junk.shape)\n","print(g_scan.shape)\n","print(g_tcp.shape)\n","print(g_udp.shape)"],"execution_count":4,"outputs":[{"output_type":"stream","text":["(45930, 115)\n","(111480, 115)\n","(125715, 115)\n","(151879, 115)\n","(78244, 115)\n","(54283, 115)\n","(28579, 115)\n","(27825, 115)\n","(88816, 115)\n","(103720, 115)\n"],"name":"stdout"}]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"IL0f3rd_o-DL","executionInfo":{"status":"ok","timestamp":1625203467233,"user_tz":-600,"elapsed":75,"user":{"displayName":"Jane ZOU","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GhovXuga2ucGkqSP_krLzx1k4yHH4hCC5bJTF0L=s64","userId":"02928433389786515403"}},"outputId":"32c40e6f-947e-49d6-96b8-622e22d11f70"},"source":["benign.info()"],"execution_count":5,"outputs":[{"output_type":"stream","text":["<class 'pandas.core.frame.DataFrame'>\n","RangeIndex: 46585 entries, 0 to 46584\n","Columns: 115 entries, MI_dir_L5_weight to HpHp_L0.01_pcc\n","dtypes: float64(115)\n","memory usage: 40.9 MB\n"],"name":"stdout"}]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"lh9-vCzLo510","executionInfo":{"status":"ok","timestamp":1625203467234,"user_tz":-600,"elapsed":71,"user":{"displayName":"Jane ZOU","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GhovXuga2ucGkqSP_krLzx1k4yHH4hCC5bJTF0L=s64","userId":"02928433389786515403"}},"outputId":"966bd5b6-7466-4b60-b09d-b512b5f66573"},"source":["#missing value \n","benign.iloc[:,:60].isna().any(),benign.iloc[:,60:].isna().any()"],"execution_count":6,"outputs":[{"output_type":"execute_result","data":{"text/plain":["(MI_dir_L5_weight         False\n"," MI_dir_L5_mean           False\n"," MI_dir_L5_variance       False\n"," MI_dir_L3_weight         False\n"," MI_dir_L3_mean           False\n"," MI_dir_L3_variance       False\n"," MI_dir_L1_weight         False\n"," MI_dir_L1_mean           False\n"," MI_dir_L1_variance       False\n"," MI_dir_L0.1_weight       False\n"," MI_dir_L0.1_mean         False\n"," MI_dir_L0.1_variance     False\n"," MI_dir_L0.01_weight      False\n"," MI_dir_L0.01_mean        False\n"," MI_dir_L0.01_variance    False\n"," H_L5_weight              False\n"," H_L5_mean                False\n"," H_L5_variance            False\n"," H_L3_weight              False\n"," H_L3_mean                False\n"," H_L3_variance            False\n"," H_L1_weight              False\n"," H_L1_mean                False\n"," H_L1_variance            False\n"," H_L0.1_weight            False\n"," H_L0.1_mean              False\n"," H_L0.1_variance          False\n"," H_L0.01_weight           False\n"," H_L0.01_mean             False\n"," H_L0.01_variance         False\n"," HH_L5_weight             False\n"," HH_L5_mean               False\n"," HH_L5_std                False\n"," HH_L5_magnitude          False\n"," HH_L5_radius             False\n"," HH_L5_covariance         False\n"," HH_L5_pcc                False\n"," HH_L3_weight             False\n"," HH_L3_mean               False\n"," HH_L3_std                False\n"," HH_L3_magnitude          False\n"," HH_L3_radius             False\n"," HH_L3_covariance         False\n"," HH_L3_pcc                False\n"," HH_L1_weight             False\n"," HH_L1_mean               False\n"," HH_L1_std                False\n"," HH_L1_magnitude          False\n"," HH_L1_radius             False\n"," HH_L1_covariance         False\n"," HH_L1_pcc                False\n"," HH_L0.1_weight           False\n"," HH_L0.1_mean             False\n"," HH_L0.1_std              False\n"," HH_L0.1_magnitude        False\n"," HH_L0.1_radius           False\n"," HH_L0.1_covariance       False\n"," HH_L0.1_pcc              False\n"," HH_L0.01_weight          False\n"," HH_L0.01_mean            False\n"," dtype: bool, HH_L0.01_std             False\n"," HH_L0.01_magnitude       False\n"," HH_L0.01_radius          False\n"," HH_L0.01_covariance      False\n"," HH_L0.01_pcc             False\n"," HH_jit_L5_weight         False\n"," HH_jit_L5_mean           False\n"," HH_jit_L5_variance       False\n"," HH_jit_L3_weight         False\n"," HH_jit_L3_mean           False\n"," HH_jit_L3_variance       False\n"," HH_jit_L1_weight         False\n"," HH_jit_L1_mean           False\n"," HH_jit_L1_variance       False\n"," HH_jit_L0.1_weight       False\n"," HH_jit_L0.1_mean         False\n"," HH_jit_L0.1_variance     False\n"," HH_jit_L0.01_weight      False\n"," HH_jit_L0.01_mean        False\n"," HH_jit_L0.01_variance    False\n"," HpHp_L5_weight           False\n"," HpHp_L5_mean             False\n"," HpHp_L5_std              False\n"," HpHp_L5_magnitude        False\n"," HpHp_L5_radius           False\n"," HpHp_L5_covariance       False\n"," HpHp_L5_pcc              False\n"," HpHp_L3_weight           False\n"," HpHp_L3_mean             False\n"," HpHp_L3_std              False\n"," HpHp_L3_magnitude        False\n"," HpHp_L3_radius           False\n"," HpHp_L3_covariance       False\n"," HpHp_L3_pcc              False\n"," HpHp_L1_weight           False\n"," HpHp_L1_mean             False\n"," HpHp_L1_std              False\n"," HpHp_L1_magnitude        False\n"," HpHp_L1_radius           False\n"," HpHp_L1_covariance       False\n"," HpHp_L1_pcc              False\n"," HpHp_L0.1_weight         False\n"," HpHp_L0.1_mean           False\n"," HpHp_L0.1_std            False\n"," HpHp_L0.1_magnitude      False\n"," HpHp_L0.1_radius         False\n"," HpHp_L0.1_covariance     False\n"," HpHp_L0.1_pcc            False\n"," HpHp_L0.01_weight        False\n"," HpHp_L0.01_mean          False\n"," HpHp_L0.01_std           False\n"," HpHp_L0.01_magnitude     False\n"," HpHp_L0.01_radius        False\n"," HpHp_L0.01_covariance    False\n"," HpHp_L0.01_pcc           False\n"," dtype: bool)"]},"metadata":{"tags":[]},"execution_count":6}]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"9cm3cXb1o_Tr","executionInfo":{"status":"ok","timestamp":1625203467239,"user_tz":-600,"elapsed":65,"user":{"displayName":"Jane ZOU","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GhovXuga2ucGkqSP_krLzx1k4yHH4hCC5bJTF0L=s64","userId":"02928433389786515403"}},"outputId":"ecbb1f28-62ca-4ed3-c717-bba3e5c580bb"},"source":["#checking if all the files have the same features \n","print(g_combo.columns == benign.columns)\n","print(g_combo.columns == m_ack.columns)"],"execution_count":7,"outputs":[{"output_type":"stream","text":["[ True  True  True  True  True  True  True  True  True  True  True  True\n","  True  True  True  True  True  True  True  True  True  True  True  True\n","  True  True  True  True  True  True  True  True  True  True  True  True\n","  True  True  True  True  True  True  True  True  True  True  True  True\n","  True  True  True  True  True  True  True  True  True  True  True  True\n","  True  True  True  True  True  True  True  True  True  True  True  True\n","  True  True  True  True  True  True  True  True  True  True  True  True\n","  True  True  True  True  True  True  True  True  True  True  True  True\n","  True  True  True  True  True  True  True  True  True  True  True  True\n","  True  True  True  True  True  True  True]\n","[ True  True  True  True  True  True  True  True  True  True  True  True\n","  True  True  True  True  True  True  True  True  True  True  True  True\n","  True  True  True  True  True  True  True  True  True  True  True  True\n","  True  True  True  True  True  True  True  True  True  True  True  True\n","  True  True  True  True  True  True  True  True  True  True  True  True\n","  True  True  True  True  True  True  True  True  True  True  True  True\n","  True  True  True  True  True  True  True  True  True  True  True  True\n","  True  True  True  True  True  True  True  True  True  True  True  True\n","  True  True  True  True  True  True  True  True  True  True  True  True\n","  True  True  True  True  True  True  True]\n"],"name":"stdout"}]},{"cell_type":"markdown","metadata":{"id":"IeRbXZ4SpeY2"},"source":["# Convert into one dataset"]},{"cell_type":"code","metadata":{"id":"xyhQoJRJpIvV","executionInfo":{"status":"ok","timestamp":1625203467241,"user_tz":-600,"elapsed":61,"user":{"displayName":"Jane ZOU","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GhovXuga2ucGkqSP_krLzx1k4yHH4hCC5bJTF0L=s64","userId":"02928433389786515403"}}},"source":["# add new column\n","benign['type'] = 'benign'\n","m_scan['type'] = 'm_scan'\n","m_ack['type'] = 'm_ack'\n","m_syn['type']  = 'm_syn'\n","m_udp['type'] = 'm_udp'\n","m_udpplain['type'] = 'm_udpplain'\n","g_combo['type'] = 'g_combo'\n","g_junk['type'] = 'g_junk'\n","g_scan['type'] = 'g_scan'\n","g_tcp['type'] = 'g_tcp'\n","g_udp['type'] = 'g_udp'"],"execution_count":8,"outputs":[]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"vDIuhHj3pS7f","executionInfo":{"status":"ok","timestamp":1625203467242,"user_tz":-600,"elapsed":58,"user":{"displayName":"Jane ZOU","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GhovXuga2ucGkqSP_krLzx1k4yHH4hCC5bJTF0L=s64","userId":"02928433389786515403"}},"outputId":"6b477ac1-2ffb-42b6-810d-303a6724cb05"},"source":["d = pd.concat([benign,m_scan,m_ack,m_syn,m_udp,m_udpplain,g_combo,g_junk,g_scan,g_tcp,g_udp], axis=0, sort=False, ignore_index=True)\n","d.shape"],"execution_count":9,"outputs":[{"output_type":"execute_result","data":{"text/plain":["(863056, 116)"]},"metadata":{"tags":[]},"execution_count":9}]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/","height":385},"id":"8hYBsMGvpZl4","executionInfo":{"status":"ok","timestamp":1625203467259,"user_tz":-600,"elapsed":68,"user":{"displayName":"Jane ZOU","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GhovXuga2ucGkqSP_krLzx1k4yHH4hCC5bJTF0L=s64","userId":"02928433389786515403"}},"outputId":"44ab44a3-da14-444b-c819-3215db3179d9"},"source":["#value counts\n","labels = d['type'].value_counts()\n","labels\n","label_count = pd.DataFrame({'labels': labels.index,'counts': labels.values})\n","label_count"],"execution_count":10,"outputs":[{"output_type":"execute_result","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>labels</th>\n","      <th>counts</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>0</th>\n","      <td>m_udp</td>\n","      <td>151879</td>\n","    </tr>\n","    <tr>\n","      <th>1</th>\n","      <td>m_syn</td>\n","      <td>125715</td>\n","    </tr>\n","    <tr>\n","      <th>2</th>\n","      <td>m_ack</td>\n","      <td>111480</td>\n","    </tr>\n","    <tr>\n","      <th>3</th>\n","      <td>g_udp</td>\n","      <td>103720</td>\n","    </tr>\n","    <tr>\n","      <th>4</th>\n","      <td>g_tcp</td>\n","      <td>88816</td>\n","    </tr>\n","    <tr>\n","      <th>5</th>\n","      <td>m_udpplain</td>\n","      <td>78244</td>\n","    </tr>\n","    <tr>\n","      <th>6</th>\n","      <td>g_combo</td>\n","      <td>54283</td>\n","    </tr>\n","    <tr>\n","      <th>7</th>\n","      <td>benign</td>\n","      <td>46585</td>\n","    </tr>\n","    <tr>\n","      <th>8</th>\n","      <td>m_scan</td>\n","      <td>45930</td>\n","    </tr>\n","    <tr>\n","      <th>9</th>\n","      <td>g_junk</td>\n","      <td>28579</td>\n","    </tr>\n","    <tr>\n","      <th>10</th>\n","      <td>g_scan</td>\n","      <td>27825</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>"],"text/plain":["        labels  counts\n","0        m_udp  151879\n","1        m_syn  125715\n","2        m_ack  111480\n","3        g_udp  103720\n","4        g_tcp   88816\n","5   m_udpplain   78244\n","6      g_combo   54283\n","7       benign   46585\n","8       m_scan   45930\n","9       g_junk   28579\n","10      g_scan   27825"]},"metadata":{"tags":[]},"execution_count":10}]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/","height":441},"id":"kecoeAtgppQl","executionInfo":{"status":"ok","timestamp":1625203467259,"user_tz":-600,"elapsed":63,"user":{"displayName":"Jane ZOU","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GhovXuga2ucGkqSP_krLzx1k4yHH4hCC5bJTF0L=s64","userId":"02928433389786515403"}},"outputId":"f228a1fd-531e-4915-a659-ac2d46e9897b"},"source":["labels = label_count['labels']\n","sizes = label_count['counts']\n","plt.figure(figsize=(8,6))\n","colors = ['red', 'orange', 'yellow', 'green', 'blue', 'lightskyblue', 'pink', 'purple', 'rosybrown', 'olive', 'darkgrey']\n","# colors = [1,2,3,4,5,6,7,8,9,10,11]\n","explode = (0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.1)\n","patches, texts = plt.pie(sizes, explode = explode, colors=colors, shadow=True, startangle=100, pctdistance=100, labeldistance=10)\n","plt.legend(patches, labels, loc=\"best\")\n","plt.axis('equal')\n","plt.tight_layout()\n","plt.show()"],"execution_count":11,"outputs":[{"output_type":"display_data","data":{"image/png":"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\n","text/plain":["<Figure size 576x432 with 1 Axes>"]},"metadata":{"tags":[]}}]},{"cell_type":"markdown","metadata":{"id":"qcuz3bkap0-r"},"source":["# Save dataset"]},{"cell_type":"code","metadata":{"id":"JkF4Keo5pwsz","executionInfo":{"status":"ok","timestamp":1625203672328,"user_tz":-600,"elapsed":109950,"user":{"displayName":"Jane ZOU","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GhovXuga2ucGkqSP_krLzx1k4yHH4hCC5bJTF0L=s64","userId":"02928433389786515403"}}},"source":["d.to_csv('/content/drive/MyDrive/5703 CP/Device #8.csv')"],"execution_count":13,"outputs":[]},{"cell_type":"code","metadata":{"id":"Od59ThoLrlSm"},"source":[""],"execution_count":null,"outputs":[]}]}