Intrusion detection based on rough set and artificial immune

被引:0
|
作者
张玲 [1 ]
Sun Haiyan [1 ]
Cui Jiantao [1 ]
Yang Hua [1 ]
Huang Yan [1 ]
机构
[1] Software Engineering College,Zhengzhou University of Light Industry
基金
中国国家自然科学基金;
关键词
rough set; artificial immune; anomaly intrusion detection; rough set and artificial immune(RSAI-IDA);
D O I
暂无
中图分类号
TP18 [人工智能理论]; TP393.08 [];
学科分类号
081104 ; 0812 ; 0835 ; 0839 ; 1402 ; 1405 ;
摘要
In order to increase intrusion detection rate and decrease false positive detection rate,a novel intrusion detection algorithm based on rough set and artificial immune( RSAI-IDA) is proposed.Using artificial immune in intrusion detection,anomaly actions are detected adaptively,and with rough set,effective antibodies can be obtained. A scheme,in which antibodies are partly generated randomly and others are from the artificial immune algorithm,is applied to ensure the antibodies diversity. Finally,simulations of RSAI-IDA and comparisons with other algorithms are given. The experimental results illustrate that the novel algorithm achieves more effective performances on anomaly intrusion detection,where the algorithm’s time complexity decreases,the true positive detection rate increases,and the false positive detection rate is decreased.
引用
收藏
页码:368 / 375
页数:8
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