A Matrix Negative Selection Algorithm for Anomaly Detection

被引：2
|
作者：
Yi, Zhaoxiang [1 ]
Mu, Xiaodong [1 ]
Zhang, Li [1 ]
Zhao, Peng [1 ]
机构：
[1] Xian Res Inst High Tech, Dept Comp, Xian 710025, Peoples R China
来源：
2008 IEEE CONGRESS ON EVOLUTIONARY COMPUTATION, VOLS 1-8 | 2008年
关键词：
D O I：
10.1109/CEC.2008.4630915
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
This paper presents a matrix negative selection algorithm for anomaly detection. The proposed algorithm is a twofold improvement over conventional negative selection algorithms. In matrix representation, characteristics of the self set are emerged by multiple vectors to distinctly express the boundary of self and non-self. On the other hand, based on the matrix matching coefficient, separate match rules for generating detectors and monitoring anomaly are designed to avoid the sharp distinction caused by threshold. Results have demonstrated that the matrix negative selection algorithm is effective and reliable for anomaly detection and suitable for small sample problems of complex systems.
引用
收藏
页码：978 / 983
页数：6
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