Multi-objective Functions in Particle Swarm Optimization for Intrusion Detection

被引：0
作者：
Cleetus, Nimmy [1 ]
Dhanya, K. A. [1 ]
机构：
[1] SCMS Sch Engn & Technol, Dept Comp Sci & Engn, Ernakulam, Kerala, India
来源：
2014 INTERNATIONAL CONFERENCE ON ADVANCES IN COMPUTING, COMMUNICATIONS AND INFORMATICS (ICACCI) | 2014年
关键词：
Particle Swarm Optimization; multi-objective functions; intrusion detection; fitness function;
D O I：
暂无
中图分类号：
TP301 [理论、方法];
学科分类号：
081202 ;
摘要：
The paper constitutes the study of particle swarm optimization in multi-objective functions. Swarm intelligence plays a vital role in intrusion detection. Intrusion detection system identifies the normal as well as abnormal behavior of a system. The weighted aggregation method is considered as multi-objective functions. We propose an intrusion detection mechanism based on particle swarm optimization which has a strong global search capability and used for the dimensionality optimization. Random forest is used as the classifier for modelling attacks and legitimate set. An accuracy of 91.71% at detection time of 0.22sec is obtained.
引用
收藏
页码：387 / 392
页数：6
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