Journal of Beijing University of Posts and Telecommunications

  • EI核心期刊

JOURNAL OF BEIJING UNIVERSITY OF POSTS AND TELECOM ›› 2013, Vol. 36 ›› Issue (3): 39-43.doi: 10.13190/jbupt.201303.41.lutl

• Papers • Previous Articles     Next Articles

Virus Detection Model Based on Dynamic Clonal Selection Algorithm

LU Tian-liang1,2, ZHENG Kang-feng1, LIU Ying-qing1, HU Ying3, WU Bin1   

  1. 1. Information Security Center, Beijing University of Posts and Telecommunications, Beijing 100876, China;
    2. School of Network Security Defense, People’s Public Security University of China, Beijing 100038, China;
    3. Beijing Command College of Chinese People’s Armed Police Force, Beijing 100012, China
  • Received:2012-09-18 Online:2013-06-30 Published:2013-06-30

Abstract:

In order to detect virus variants and unknown viruses effectively, inspired by the biological immune system, a computer virus detection model based on artificial immune systems (AIS) is proposed. The dynamic clonal selection algorithm is improved to solve the problem that the self-space is static during the training. The proposed model has enhanced the adaptability of virus detection systems to the continuously changing virus environment. Experiment shows that the proposed model has good adaptabilities, it can effectively detect viruses and has a low false positive rate.

Key words: virus detection, artificial immune system, dynamic clonal selection algorithm

CLC Number: