Training code

temp.py

+# -*- coding: utf-8 -*-
+"""
+Spyder Editor
+
+This is a temporary script file.
+"""
+
+#importing dataset
+
+import pandas as pd
+import matplotlib.pyplot as plt
+import numpy as np
+import seaborn as sn 
+
+dataset = pd.read_csv('DrDoS_NTP.csv') 
+
+#EDA
+
+dataset.head()
+dataset.columns
+dataset.head
+dataset.describe()
+
+#cleaning
+
+dataset.isna().any()
+
+
+#encoding 
+
+dataset = pd.get_dummies(dataset)
+dataset.columns
+dataset = dataset.drop(columns = [' Timestamp','Fwd PSH Flags',' Bwd PSH Flags',' Fwd URG Flags',' Bwd URG Flags'])
+
+
+#remove extra column
+
+attack_id = dataset['Flow ID']
+d_port = dataset[' Destination Port']
+state = dataset[' Inbound']
+dataset = dataset.drop(columns = ['Flow ID',' Destination Port',' Inbound'])
+
+#deviding into traing and testing
+
+from sklearn.model_selection import train_test_split
+X_train, X_test, y_train, y_test = train_test_split(dataset,state,test_size = 1, random_state = 0)
+
+
+# feture scaling
+from sklearn.preprocessing import StandardScaler
+sc_X = StandardScaler()
+X_train2 = pd.DataFrame(sc_X.fit_transform(X_train))
+X_test2 = pd.DataFrame(sc_X.transform(X_test))
+X_train2.columns = X_train.columns.values
+X_test2.columns = X_test.columns.values
+X_train2.index = X_train.index.values
+X_test2.index = X_test.index.values
+X_train = X_train2
+X_test = X_test2 
+
+## SVM (Linear)
+from sklearn.svm import SVC
+classifier = SVC(random_state = 0, kernel = 'linear')
+classifier.fit(X_train,y_train)
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