[1]TAN Ying,ZHANG Pengtao.Immune based computer virus detection approaches[J].CAAI Transactions on Intelligent Systems,2013,8(1):80-94.[doi:10.3969/j.issn.1673-4785.201209059]
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Immune based computer virus detection approaches

CAAI Transactions on Intelligent Systems[ISSN 1673-4785/CN 23-1538/TP] Volume: 8 Number of periods: 2013 1 Page number: 80-94 Column: 学术论文—机器学习 Public date: 2013-03-25
Title:
Immune based computer virus detection approaches
Author(s):
TAN Ying1; 2;  ZHANG Pengtao1; 2
1. Department of Machine Intelligence, School of Electronics Engineering and Computer Science, Peking University, Beijing 100871, China;
?2. Key Laboratory of Machine Perception, Ministry of Education, Peking University, Beijing 100871, China
Keywords:
computer virus detection;  artificial immune system;  immune algorithms;  hierarchical model;  negative selection algorithm with penalty factor
CLC:
TP309.5
DOI:
10.3969/j.issn.1673-4785.201209059
Abstract:
The computer virus is considered one of the most horrifying threats to the security of computer systems worldwide. The rapid development of evasion techniques used in virus causes the signature based computer virus detection techniques to be ineffective. Many novel computer virus detection approaches have been proposed in the past to cope with the ineffectiveness, mainly classified into three categories: static, dynamic and heuristics techniques. As the natural similarities between the biological immune system (BIS), computer security system (CSS), and the artificial immune system (AIS) were all developed as a new prototype in the community of antivirus research. The immune mechanisms in the BIS provide the opportunities to construct computer virus detection models that are robust and adaptive with the ability to detect unseen viruses. In this paper, a variety of classic computer virus detection approaches were introduced and reviewed based on the background knowledge of the computer virus history. Next, a variety of immune based computer virus detection approaches were also discussed in detail. Promising experimental results suggest that the immune based computer virus detection approaches were able to detect new variants and unseen viruses at lower false positive rates, which have paved a new way for the antivirus research.
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