convert_original_datasets/Convert for Device 2.ipynb

{"nbformat":4,"nbformat_minor":0,"metadata":{"colab":{"name":"Convert for Device 2.ipynb","provenance":[],"toc_visible":true,"authorship_tag":"ABX9TyOrEgKXTD2sq+KiSY2Kt+rm"},"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":1625205112351,"user_tz":-600,"elapsed":23825,"user":{"displayName":"Jane ZOU","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GhovXuga2ucGkqSP_krLzx1k4yHH4hCC5bJTF0L=s64","userId":"02928433389786515403"}},"outputId":"247a7ee6-2004-439d-f68b-9afc1400a53d"},"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":1625205112769,"user_tz":-600,"elapsed":453,"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":1625205146065,"user_tz":-600,"elapsed":33299,"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/2.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/2.mirai.scan.csv')\n","m_ack = pd.read_csv('/content/drive/MyDrive/5703 CP/Datasets/2.mirai.ack.csv')\n","m_syn = pd.read_csv('/content/drive/MyDrive/5703 CP/Datasets/2.mirai.syn.csv')\n","m_udp = pd.read_csv('/content/drive/MyDrive/5703 CP/Datasets/2.mirai.udp.csv')\n","m_udpplain = pd.read_csv('/content/drive/MyDrive/5703 CP/Datasets/2.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/2.gafgyt.scan.csv')\n","g_junk = pd.read_csv('/content/drive/MyDrive/5703 CP/Datasets/2.gafgyt.junk.csv')\n","g_udp = pd.read_csv('/content/drive/MyDrive/5703 CP/Datasets/2.gafgyt.udp.csv')\n","g_tcp = pd.read_csv('/content/drive/MyDrive/5703 CP/Datasets/2.gafgyt.tcp.csv')\n","g_combo = pd.read_csv('/content/drive/MyDrive/5703 CP/Datasets/2.gafgyt.combo.csv')"],"execution_count":3,"outputs":[]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"QxlE1MfhorlX","executionInfo":{"status":"ok","timestamp":1625205146066,"user_tz":-600,"elapsed":47,"user":{"displayName":"Jane ZOU","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GhovXuga2ucGkqSP_krLzx1k4yHH4hCC5bJTF0L=s64","userId":"02928433389786515403"}},"outputId":"27119914-398f-4ee4-83c0-c0a3f3420dca"},"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":["(43192, 115)\n","(113285, 115)\n","(116807, 115)\n","(151481, 115)\n","(87368, 115)\n","(53012, 115)\n","(30312, 115)\n","(27494, 115)\n","(95021, 115)\n","(104791, 115)\n"],"name":"stdout"}]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"IL0f3rd_o-DL","executionInfo":{"status":"ok","timestamp":1625205146067,"user_tz":-600,"elapsed":41,"user":{"displayName":"Jane ZOU","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GhovXuga2ucGkqSP_krLzx1k4yHH4hCC5bJTF0L=s64","userId":"02928433389786515403"}},"outputId":"fd2c0135-6ec8-45a5-e69d-96ef186ea153"},"source":["benign.info()"],"execution_count":5,"outputs":[{"output_type":"stream","text":["<class 'pandas.core.frame.DataFrame'>\n","RangeIndex: 13113 entries, 0 to 13112\n","Columns: 115 entries, MI_dir_L5_weight to HpHp_L0.01_pcc\n","dtypes: float64(115)\n","memory usage: 11.5 MB\n"],"name":"stdout"}]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"lh9-vCzLo510","executionInfo":{"status":"ok","timestamp":1625205146068,"user_tz":-600,"elapsed":34,"user":{"displayName":"Jane ZOU","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GhovXuga2ucGkqSP_krLzx1k4yHH4hCC5bJTF0L=s64","userId":"02928433389786515403"}},"outputId":"934e0b7f-24dc-4c8c-bda0-798a9d567c99"},"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":1625205146069,"user_tz":-600,"elapsed":16,"user":{"displayName":"Jane ZOU","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GhovXuga2ucGkqSP_krLzx1k4yHH4hCC5bJTF0L=s64","userId":"02928433389786515403"}},"outputId":"679a8f22-16c5-402f-a6dc-972e539343d0"},"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":1625205146069,"user_tz":-600,"elapsed":10,"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":1625205146611,"user_tz":-600,"elapsed":552,"user":{"displayName":"Jane ZOU","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GhovXuga2ucGkqSP_krLzx1k4yHH4hCC5bJTF0L=s64","userId":"02928433389786515403"}},"outputId":"f3a74160-f10e-480e-8201-29fb1f484295"},"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":["(835876, 116)"]},"metadata":{"tags":[]},"execution_count":9}]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/","height":385},"id":"8hYBsMGvpZl4","executionInfo":{"status":"ok","timestamp":1625205146635,"user_tz":-600,"elapsed":30,"user":{"displayName":"Jane ZOU","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GhovXuga2ucGkqSP_krLzx1k4yHH4hCC5bJTF0L=s64","userId":"02928433389786515403"}},"outputId":"0cf5c38a-09a5-46df-b4c3-3f66c2db88e0"},"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>151481</td>\n","    </tr>\n","    <tr>\n","      <th>1</th>\n","      <td>m_syn</td>\n","      <td>116807</td>\n","    </tr>\n","    <tr>\n","      <th>2</th>\n","      <td>m_ack</td>\n","      <td>113285</td>\n","    </tr>\n","    <tr>\n","      <th>3</th>\n","      <td>g_udp</td>\n","      <td>104791</td>\n","    </tr>\n","    <tr>\n","      <th>4</th>\n","      <td>g_tcp</td>\n","      <td>95021</td>\n","    </tr>\n","    <tr>\n","      <th>5</th>\n","      <td>m_udpplain</td>\n","      <td>87368</td>\n","    </tr>\n","    <tr>\n","      <th>6</th>\n","      <td>g_combo</td>\n","      <td>53012</td>\n","    </tr>\n","    <tr>\n","      <th>7</th>\n","      <td>m_scan</td>\n","      <td>43192</td>\n","    </tr>\n","    <tr>\n","      <th>8</th>\n","      <td>g_junk</td>\n","      <td>30312</td>\n","    </tr>\n","    <tr>\n","      <th>9</th>\n","      <td>g_scan</td>\n","      <td>27494</td>\n","    </tr>\n","    <tr>\n","      <th>10</th>\n","      <td>benign</td>\n","      <td>13113</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>"],"text/plain":["        labels  counts\n","0        m_udp  151481\n","1        m_syn  116807\n","2        m_ack  113285\n","3        g_udp  104791\n","4        g_tcp   95021\n","5   m_udpplain   87368\n","6      g_combo   53012\n","7       m_scan   43192\n","8       g_junk   30312\n","9       g_scan   27494\n","10      benign   13113"]},"metadata":{"tags":[]},"execution_count":10}]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/","height":441},"id":"kecoeAtgppQl","executionInfo":{"status":"ok","timestamp":1625205147438,"user_tz":-600,"elapsed":831,"user":{"displayName":"Jane ZOU","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GhovXuga2ucGkqSP_krLzx1k4yHH4hCC5bJTF0L=s64","userId":"02928433389786515403"}},"outputId":"ae5ff5f1-77ea-4834-981c-0c33571007fb"},"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":1625205274590,"user_tz":-600,"elapsed":127160,"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 #2.csv')"],"execution_count":12,"outputs":[]}]}