基于机器学习的入侵检测系统

The Intrusion Detetection System Based On Mechine Learning

针对现有入侵检测系统存在的不足,研究了基于网络和误用的入侵检测系统Snort,提出了基于机器学习的Snort系统方案,使Snort不仅能通过模式匹配的方式检测到一些已知的攻击,还能通过自我学习检测到未知的攻击。

Aiming at some problems in current intrusion detection technique, this paper proposes a general intrusion detection system based on machine learning, and researches on the intrusion detection systenl - Snort based on the network and misuse. A plan of Snort learning systein based on the machine is put forward, so that the machine learning - based .Snort system can not （rely detect the known attacks by pattern matching, hut also detect the unknown attacks by self learning.