# web《Web安全之机器学习入门》实现代码

实现代码并加入注释

## 目录


- [5-3-KNN检测异常操作](5-3-KNN-detect-abnormal-operation.py)
- [5-4-KNN检测异常操作(二)](5-4-KNN-detect-abnormal-operation.py)
- [5-5-KNN检测Rootkit](5-5-KNN-detect-Rootkit.py)
- [5-6-KNN检测Webshell](5-6-KNN-detect-Webshell.py)
- [6-1-决策树训练-导出决策树](6-1-DecisionTree-train-and-export.py)
- [6-3-决策树检测POP3暴力破解](6-3-DecisionTree-detect-POP3-attack.py)
- [6-4-决策树检测FTP暴力破解](6-4-DecisionTree-detect-FTP-attack.py)
- [6-5-随机森林检测FTP暴力破解](6-5-RandomForest-detect-FTP-attack.py)
- [7-3-朴素贝叶斯检测异常操作](7-3-NaiveBayesian-detect-abnormal-operation.py)
- [7-4-朴素贝叶斯检测WEBSHELL](7-4-NaiveBayesian-detect-WEBSHELL.py)
- [7-5-朴素贝叶斯检测WEBSHELL(二)](7-5-NaiveBayesian-detect-WEBSHELL.py)
- [7-6-朴素贝叶斯检测DGA域名](7-6-NaiveBayesian-detect-DGA-domain.py)
- [7-7-朴素贝叶斯检测对Apache的DDoS攻击](7-7-NaiveBayesian-detect-Apache-DDoS.py)
- [7-8-朴素贝叶斯识别验证码](7-8-NaiveBayesian-recognise-images.py)
- [8-2-逻辑回归demo](8-2-LogisticRegression-demo.py)
- [8-3-逻辑回归检测Java溢出攻击](8-3-LogisticRegression-detect-java-buffer-overflow-attack.py)
- [8-4-逻辑回归识别验证码](8-4-LogisticRegression-recognise-images.py)
- [9-2-支持向量机demo](9-2-SVM-demo.py)
- [9-3-支持向量机识别XSS](9-3-SVM-recognise-XSS.py)
- [9-4-支持向量机区分僵尸网络DGA家族](9-4-SVM-discriminate-DGA.py)
- [10-2-K均值demo](10-2-Kmeans-demo.py)
- [10-3-K均值区分僵尸网络DGA家族](10-3-Kmeans-discriminate-DGA.py)
- [10-4-DBSCAN-demo](10-4-DBSCAN-demo.py)
- [11-1-Apriori-demo](11-1-Apriori-demo.py)
- [11-2-Apriori挖掘XSS相关参数](11-2-Apriori-Mining-XSS-param.py)
- [11-3-FP-growth-demo](11-3-FP-growth-demo.py)
- [11-4-FP-growth-挖掘疑似僵尸主机](11-4-FP-growth-Mining-Zombie-Computer.py)
- [12-2-隐式马尔可夫-demo](12-2-HMM-demo.py)
- [12-3-隐式马尔可夫-识别XSS](12-3-HMM-recognise-XSS.py)
- [12-4-隐式马尔可夫-识别XSS(二)](12-4-隐式马尔可夫-识别XSS(二).py)
- [12-5-隐式马尔可夫-识别DGA域名](12-5-HMM-recognise-DGA.py)
- [13-2-图算法-demo](13-2-Graph-algorithm-demo.py)
- [13-3-图算法-识别WebShell](13-3-Graph-algorithm-recognise-WebShell.py)
- [13-4-图算法-识别僵尸网络](13-4-Graph-algorithm-recognise-Botnet.py)
- [13-6-知识图谱-风控领域的应用](13-6-knowledge-graph-Risk-Control.py)
- [13-7-知识图谱-威胁情报领域的应用](13-7-knowledge-graph-Threat-Intelligence.py)
- [14-2-神经网络-demo](14-2-NN-demo.py)
- [14-3-神经网络-识别验证码](14-3-NN-recognise-images.py)
- [14-4-神经网络-检测Java溢出攻击](14-4-NN-detect-java-buffer-overflow-attack.py)
- [15-4-深度神经网络-识别验证码-softmax回归算法](15-4-DNN-recognise-images-softmax.py)
- [15-5-深度神经网络-识别验证码-DNN](15-5-DNN-recognise-images-DNN.py)
- [15-6-深度神经网络-识别验证码-多层感知机](15-6-DNN-recognise-images-MLP.py)
- [15-7-朴素贝叶斯算法-识别垃圾邮件](15-7-NaiveBayesian-recognise-junk-mail.py)
- [15-8-深度神经网络-识别垃圾邮件-DNN](15-8-DNN-recognise-junk-mail.py)
- [16-2-循环神经网络-识别验证码-LSTM](16-2-RNN-recognise-images-LSTM.py)
- [16-3-循环神经网络-识别恶意评论-LSTM](16-3-RNN-recognise-malicious-comments-LSTM.py)
- [16-3-朴素贝叶斯-识别恶意评论-NB](16-3-NaiveBayesian-recognise-malicious-comments.py)
- [16-4-循环神经网络-生成城市名称-LSTM](16-4-RNN-Generate-city-name-LSTM.py)
- [16-5-循环神经网络-识别WebShell-LSTM](16-5-RNN-recognise-WebShell-LSTM.py)
- [16-6-循环神经网络-生成常用密码-LSTM](16-6-RNN-Generate-password-LSTM.py)
- [16-7-循环神经网络-识别异常操作-LSTM](16-7-RNN-recognise-abnormal-operation-LSTM.py)
- [17-2-卷积神经网络-demo](17-2-CNN-demo.py)
- [17-3-卷积神经网络-识别恶意评论](17-3-CNN-recognise-malicious-comments.py)
- [17-4-卷积神经网络-识别垃圾邮件](17-4-CNN-recognise-junk-mail.py)