文章基本信息

标题：Real-valued Dual Negative Selection Technique for Intrusion Detection
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作者：Niu Ling ; Feng Gao Feng
期刊名称：International Journal of Security and Its Applications
印刷版ISSN：1738-9976
出版年度：2015
卷号：9
期号：4
页码：279-288
DOI：10.14257/ijsia.2015.9.4.26
出版社：SERSC
摘要：A novel technique for intrusion detection based on real-valued dual negative selection scheme is proposed in this paper. In traditional real-valued negative selection algorithms, whether the candidate detectors can detect self-set or not totally relies on the affinity extent and the constant-sized mechanism is unfavorable to eliminating the black holes with irregular sizes. The proposed technique introduces the mechanism of variable-sized dual negative selection, in which each mutual detector has to pass three tests. Firstly, the new mutual detector should not be detected by the current existing ones. In other words, the existence of the new detector is necessary. Secondly, those detectors which can detect self-set will be eliminated. Thirdly, the detectors distribution has to be optimized aiming at enhancing the detecting efficiency. Experimental results demonstrate that the proposed technique has much less black holes, fewer detectors and higher detecting rates.
关键词：intrusion detection; real-valued; negative selection; detector; variable-sized