中国邮电高校学报(英文) ›› 2014, Vol. 21 ›› Issue (2): 83-90.doi: 10.1016/S1005-8885(14)60290-9

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Integrated intrusion detection model based on artificial immune

张玲1,白中英2 ,LU Yun-long1, ZHA Ya-xing1, LI Zhen-wen1   

  1. 1. 北京邮电大学
    2. 北京邮电大学计算机分院
  • 收稿日期:2013-10-08 修回日期:2014-03-11 出版日期:2014-04-30 发布日期:2014-04-30
  • 通讯作者: 张玲 E-mail:ll790217@163.com
  • 基金资助:

    通信网的网络理论和技术

Integrated intrusion detection model based on artificial immune

  1. 1. School of Computer Science, Beijing University of Posts and Telecommunications, Beijing 100876, China 2. Zhengzhou University of Light Industry, Zhengzhou 450000, China
  • Received:2013-10-08 Revised:2014-03-11 Online:2014-04-30 Published:2014-04-30
  • Contact: Zhang ling E-mail:ll790217@163.com
  • Supported by:

    the National Natural Science Foundation of China (61161140320).

摘要:

The author puts forward an integrated intrusion detection (ID) model based on artificial immune (IIDAI), a vaccination strategy based on the significance degree of genes and a method to generate initial memory antibodies with rough set (RS). IIDAI integrates two kinds of intrusion detection mode: misuse detection and anonymous detection. Misuse detection and anonymous detection are applied to detect the known and the unknown attacks, respectively. On the basis of IIDAI model, an ID algorithm is presented. Simulation shows that the IIDAI has better performance than traditional ID methods in feasibility and effectiveness. It is very prone to achieve a higher convergence rate by using the vaccination strategy. Moreover, RS can remove the redundancy attributes and increase the detection speed. It can also increase detection rate by applying the integrated method.

关键词:

ID, RS, artificial immune, vaccination

Abstract:

The author puts forward an integrated intrusion detection (ID) model based on artificial immune (IIDAI), a vaccination strategy based on the significance degree of genes and a method to generate initial memory antibodies with rough set (RS). IIDAI integrates two kinds of intrusion detection mode: misuse detection and anonymous detection. Misuse detection and anonymous detection are applied to detect the known and the unknown attacks, respectively. On the basis of IIDAI model, an ID algorithm is presented. Simulation shows that the IIDAI has better performance than traditional ID methods in feasibility and effectiveness. It is very prone to achieve a higher convergence rate by using the vaccination strategy. Moreover, RS can remove the redundancy attributes and increase the detection speed. It can also increase detection rate by applying the integrated method.

Key words:

ID, RS, artificial immune, vaccination

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