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A study of detector generation algorithms based on artificial immune in intrusion detection system

机译:基于人工免疫入侵检测系统的检测器生成算法研究

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Detector plays an important role in self and non-self discrimination for intrusion detection system, which makes detector generation a kernel algorithm for artificial immune system. In this paper, firstly current used binary matching rules are listed, characteristics of which are analyzed. And detector generation algorithm is divided into three main processes, including gene library, negative selection and clone selection. Evolution for gene library is explained based on the gene library theory. Several new methods are adopted to improve the performance of NSA, and finally cooperative co-evolution detector generation model is constructed which is a novel structure for intrusion detection system. This paper is aimed for researchers to focus problems on three main ideas concluded in last chapter.
机译:检测器在入侵检测系统的自我和非自我识别中起着重要的作用,这使得检测器的生成成为人工免疫系统的核心算法。在本文中,首先列出了当前使用的二进制匹配规则,并分析了其特征。检测器生成算法分为基因库,阴性选择和克隆选择三个主要过程。基于基因库理论解释了基因库的进化。为了提高NSA的性能,采用了几种新的方法,最后建立了协同协同进化检测器生成模型,为入侵检测系统提供了一种新颖的结构。本文旨在使研究人员将问题集中在上一章总结的三个主要思想上。

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