机器学习在网络安全入侵检测中的应用

Application of Machine Learning in Network Security Intrusion Detection

网络入侵检测技术能够对系统进行实时检测或事后检测,及时发现、防范各种复杂多变的网络攻击企图、攻击行为与攻击结果。同时网络入侵检测技术也是网络空间安全中一个具有挑战性的网络安全问题,机器学习对入侵检测技术性能的提高成为热门研究内容。文章综述了近些年来几种典型的群体智能优化算法,及其与支持向量机相结合的网络入侵检测技术,最后对机器学习在网络安全入侵检测中的未来发展前景进行展望。

Network intrusion detection technology can detect the system in real time or after the detection,timely find and prevent various complex and changeable network attack attempts,attack behavior and attack results.At the same time,the network intrusion detection technology is also a challenging network security problem in the network space security.This paper summarizes several typical swarm intelligence optimization algorithms in recent years,and its network intrusion detection technology combined with support vector machine.Finally,the future development prospect of machine learning in network security intrusion detection is prospected.