Intrusion Detection Technology Based on Monkey Algorithm
Jiajia Zhang, Yaping Zhang, Jizhou Sun · Jisuanji gongcheng · 2011
(Abstract ) For the current Intrusion Detection System(IDS) has high false negative rate, this paper presents an intrusion detection technology based on Monkey Algorithm(MA). It uses the MA to derive a set of classification rules from network data, KDD99 data set, and the support-confidence framework is utilized as fitness function to judge the quality of each rule. The generated rules are used to detect or classify network intrusions in a real-time environment. Experimental results show that the MA-based technology can improve the quality of generating rules, so that it can improve the performance of IDS.