文章基本信息

标题：A New Approach on Intrusion Detection Based On Avidity Model Clonal Selection
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作者：N.Priya ; Sundararajan.M ; Arulselvi S 等
期刊名称：International Journal of Innovative Research in Science, Engineering and Technology
印刷版ISSN：2347-6710
电子版ISSN：2319-8753
出版年度：2015
卷号：4
期号：2
页码：587
DOI：10.15680/IJIRSET.2015.0402147
出版社：S&S Publications
摘要：To make an immune-inspired network intrusion detection system (IDS) effective, this paper proposes a new framework,which includes our avidity-model based clonal selection (AMCS) algorithm as core element. The AMCS algorithm usesan improved representation for antigens (corresponding to network access patterns) and detectors (corresponding to detection rules). Inparticular, a bio-inspired technique called gene expression programming (GEP) is integrated with artificial immune system (AIS) indetector representation. In addition, inspired by the avidity model of immunology, this paper also defines new avidity/affinity functions(corresponding to the metric for quantify the interactions between detector and antigens) that take the priorities of attribute into account.Accordingly, the proposed algorithm integrates both negative selection and positive selection with a balance factor k to assign appropriateweights to self and non-self avidity. The well known KDD CUP’99 DATA set is used for performance evaluation. The resultsshow that the intrusion detection based on AMCS provides a higher detection rate of DoS attack, a lower false alarm rate, and alower detectors generation cost. Our results indicate that breaking the bottleneck of immune-inspired network IDS through adjustingbasic elements is feasible and effective.
关键词：network intrusion detection; artificial immune system; clonal selection; avidity model; gene expression;programming