计算机工程

• 安全技术 • 上一篇    下一篇

基于人工免疫系统的入侵检测研究

方贤进,蔡妙琪   

  1. (安徽理工大学计算机学院,安徽 淮南 232001)
  • 收稿日期:2012-09-05 出版日期:2013-11-15 发布日期:2013-11-13
  • 作者简介:方贤进(1970-),男,教授、博士,主研方向:计算智能,网络安全;蔡妙琪,硕士研究生
  • 基金项目:
    国家自然科学基金资助项目(61240023)

Research on Intrusion Detection Based on Artificial Immune System

FANG Xian-jin, CAI Miao-qi   

  1. (School of Computer, Anhui University of Science and Technology, Huainan 232001, China)
  • Received:2012-09-05 Online:2013-11-15 Published:2013-11-13

摘要: 人工免疫系统(AIS)作为解决入侵检测问题的一种方法,已经显示其突出的优点并得到快速发展。为使入侵检测系统的研究者更进一步了解基于AIS的入侵检测研究进展,回顾基于第1代和第2代AIS的入侵检测常用算法,并指出算法特点。阐述树突细胞算法(DCA)适合于解决入侵检测问题的优势,给出针对DCA算法的未来研究工作,包括该算法的形式化描述、通过分片思想实现DCA在线分析组件以及DCA输入数据的自动数据预处理。

关键词: 人工免疫系统, 入侵检测, 负选择算法, 克隆选择算法, 独特型免疫网络, 树突细胞算法

Abstract: As one of the solutions to intrusion detection problem, Artificial Immune System(AIS) shows their advantages, and develops rapidly. The aim of this paper is to further know the recent advances in AIS-based intrusion detection for Intrusion Detection System(IDS) practitioners. Some of the commonly intrusion detection problem used the first and the second generation AIS paradigms are reviewed and the characteristics of each particular algorithm are demonstrated. It is shown that the Dendritic Cells Algorithm(DCA) is demonstrated the potential as a suitable candidate for intrusion detection problems. Consequently, the future works for DCA are proposed, including the formal description for the algorithm, an online analysis component to DCA based on segmentation and the automated data preprocessing for DCA input data.

Key words: Artificial Immune System(AIS), intrusion detection, negative selection algorithm, clonal selection algorithm, idiotypic immune network, Dendritic Cells Algorithm(DCA)

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