Acta Metallurgica Sinica(English letters) ›› 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

  

  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).

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

CLC Number: