数据采集与处理2017，Vol.32Issue(3)：479-488,10.DOI:10.16337/j.1004-9037.2017.03.006
机器学习在网络入侵检测中的应用
Application of Machine Learning in Network Intrusion Detection
摘要
Abstract
With the development of network,network security becomes the key course of computer research.Hacker attacks become more and more frequent.The traditional security products have loopholes.Intrusion detection,as an important means of information security,makes up for the shortcomings of the firewall,provides an effective network intrusion detection measures and protects the network security.However,there are a lot of problems in traditional network intrusion detection.Methods based on machine can detect network intrusion automatically,improve the efficiency of intrusion detection,and reduce the false negative rate and false alarm rate.Here,we first introduce some machine learning algorithms briefly,and then analyze the application of machine learning algorithm in network intrusion detection.Moreover,we compare the advantages and disadvantages of each algorithm applied in intrusion detection.Finally we summarize the application prospect of machine learning to lay the foundation for the network intrusion detection and prevention system with good performance.关键词
机器学习/网络入侵检测/决策树/神经网络/支持向量机Key words
machine learning/network intrusion detection/decision tree/neural network/support vector machine分类
信息技术与安全科学引用本文复制引用
朱琨,张琪..机器学习在网络入侵检测中的应用[J].数据采集与处理,2017,32(3):479-488,10.基金项目
江苏省自然科学基金(BK20160812)资助项目. （BK20160812）
