convert_original_datasets/Convert for Device 4.ipynb

{"nbformat":4,"nbformat_minor":0,"metadata":{"colab":{"name":"Convert for Device 4.ipynb","provenance":[],"collapsed_sections":[],"toc_visible":true,"authorship_tag":"ABX9TyOdIc5mrB1wlzyH6RS7kR/4"},"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":1625204946658,"user_tz":-600,"elapsed":23446,"user":{"displayName":"Jane ZOU","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GhovXuga2ucGkqSP_krLzx1k4yHH4hCC5bJTF0L=s64","userId":"02928433389786515403"}},"outputId":"9a8a1509-c33c-4944-a18d-816b57e91568"},"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":1625204946659,"user_tz":-600,"elapsed":9,"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":1625204993535,"user_tz":-600,"elapsed":46881,"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/4.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/4.mirai.scan.csv')\n","m_ack = pd.read_csv('/content/drive/MyDrive/5703 CP/Datasets/4.mirai.ack.csv')\n","m_syn = pd.read_csv('/content/drive/MyDrive/5703 CP/Datasets/4.mirai.syn.csv')\n","m_udp = pd.read_csv('/content/drive/MyDrive/5703 CP/Datasets/4.mirai.udp.csv')\n","m_udpplain = pd.read_csv('/content/drive/MyDrive/5703 CP/Datasets/4.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/4.gafgyt.scan.csv')\n","g_junk = pd.read_csv('/content/drive/MyDrive/5703 CP/Datasets/4.gafgyt.junk.csv')\n","g_udp = pd.read_csv('/content/drive/MyDrive/5703 CP/Datasets/4.gafgyt.udp.csv')\n","g_tcp = pd.read_csv('/content/drive/MyDrive/5703 CP/Datasets/4.gafgyt.tcp.csv')\n","g_combo = pd.read_csv('/content/drive/MyDrive/5703 CP/Datasets/4.gafgyt.combo.csv')"],"execution_count":3,"outputs":[]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"QxlE1MfhorlX","executionInfo":{"status":"ok","timestamp":1625204993536,"user_tz":-600,"elapsed":27,"user":{"displayName":"Jane ZOU","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GhovXuga2ucGkqSP_krLzx1k4yHH4hCC5bJTF0L=s64","userId":"02928433389786515403"}},"outputId":"5e9b7920-7343-4d87-e97f-8f45d1f157b7"},"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":["(103621, 115)\n","(91123, 115)\n","(118128, 115)\n","(217034, 115)\n","(80808, 115)\n","(58152, 115)\n","(28349, 115)\n","(27859, 115)\n","(92581, 115)\n","(105782, 115)\n"],"name":"stdout"}]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"IL0f3rd_o-DL","executionInfo":{"status":"ok","timestamp":1625204993537,"user_tz":-600,"elapsed":22,"user":{"displayName":"Jane ZOU","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GhovXuga2ucGkqSP_krLzx1k4yHH4hCC5bJTF0L=s64","userId":"02928433389786515403"}},"outputId":"570200ea-edac-414b-d8e1-593cffbf7cf6"},"source":["benign.info()"],"execution_count":5,"outputs":[{"output_type":"stream","text":["<class 'pandas.core.frame.DataFrame'>\n","RangeIndex: 175240 entries, 0 to 175239\n","Columns: 115 entries, MI_dir_L5_weight to HpHp_L0.01_pcc\n","dtypes: float64(115)\n","memory usage: 153.8 MB\n"],"name":"stdout"}]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"lh9-vCzLo510","executionInfo":{"status":"ok","timestamp":1625204993538,"user_tz":-600,"elapsed":18,"user":{"displayName":"Jane ZOU","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GhovXuga2ucGkqSP_krLzx1k4yHH4hCC5bJTF0L=s64","userId":"02928433389786515403"}},"outputId":"3411b277-52a3-4ab1-9a19-c0269ca1c1b5"},"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":1625204993539,"user_tz":-600,"elapsed":16,"user":{"displayName":"Jane ZOU","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GhovXuga2ucGkqSP_krLzx1k4yHH4hCC5bJTF0L=s64","userId":"02928433389786515403"}},"outputId":"f7d28e03-1003-4b7c-e4f0-da46af3cc2be"},"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":1625204993539,"user_tz":-600,"elapsed":11,"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":1625204994735,"user_tz":-600,"elapsed":1206,"user":{"displayName":"Jane ZOU","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GhovXuga2ucGkqSP_krLzx1k4yHH4hCC5bJTF0L=s64","userId":"02928433389786515403"}},"outputId":"491bce0a-9256-4dfe-c5e5-694c34a432f9"},"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":["(1098677, 116)"]},"metadata":{"tags":[]},"execution_count":9}]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/","height":385},"id":"8hYBsMGvpZl4","executionInfo":{"status":"ok","timestamp":1625204994753,"user_tz":-600,"elapsed":79,"user":{"displayName":"Jane ZOU","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GhovXuga2ucGkqSP_krLzx1k4yHH4hCC5bJTF0L=s64","userId":"02928433389786515403"}},"outputId":"4ecaab35-c969-46d3-f099-1747d1b5dd59"},"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>217034</td>\n","    </tr>\n","    <tr>\n","      <th>1</th>\n","      <td>benign</td>\n","      <td>175240</td>\n","    </tr>\n","    <tr>\n","      <th>2</th>\n","      <td>m_syn</td>\n","      <td>118128</td>\n","    </tr>\n","    <tr>\n","      <th>3</th>\n","      <td>g_udp</td>\n","      <td>105782</td>\n","    </tr>\n","    <tr>\n","      <th>4</th>\n","      <td>m_scan</td>\n","      <td>103621</td>\n","    </tr>\n","    <tr>\n","      <th>5</th>\n","      <td>g_tcp</td>\n","      <td>92581</td>\n","    </tr>\n","    <tr>\n","      <th>6</th>\n","      <td>m_ack</td>\n","      <td>91123</td>\n","    </tr>\n","    <tr>\n","      <th>7</th>\n","      <td>m_udpplain</td>\n","      <td>80808</td>\n","    </tr>\n","    <tr>\n","      <th>8</th>\n","      <td>g_combo</td>\n","      <td>58152</td>\n","    </tr>\n","    <tr>\n","      <th>9</th>\n","      <td>g_junk</td>\n","      <td>28349</td>\n","    </tr>\n","    <tr>\n","      <th>10</th>\n","      <td>g_scan</td>\n","      <td>27859</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>"],"text/plain":["        labels  counts\n","0        m_udp  217034\n","1       benign  175240\n","2        m_syn  118128\n","3        g_udp  105782\n","4       m_scan  103621\n","5        g_tcp   92581\n","6        m_ack   91123\n","7   m_udpplain   80808\n","8      g_combo   58152\n","9       g_junk   28349\n","10      g_scan   27859"]},"metadata":{"tags":[]},"execution_count":10}]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/","height":441},"id":"kecoeAtgppQl","executionInfo":{"status":"ok","timestamp":1625205245622,"user_tz":-600,"elapsed":794,"user":{"displayName":"Jane ZOU","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GhovXuga2ucGkqSP_krLzx1k4yHH4hCC5bJTF0L=s64","userId":"02928433389786515403"}},"outputId":"eb625630-af6f-4a50-9780-8fb19bb02408"},"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, 0.1, 0, 0, 0, 0, 0, 0, 0, 0, 0)\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":14,"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":1625205152984,"user_tz":-600,"elapsed":158294,"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 #4.csv')"],"execution_count":12,"outputs":[]}]}