摘要
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.
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 sys- tem (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 intro- duced 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.
出处
《智能系统学报》
CSCD
北大核心
2013年第1期80-94,共15页
CAAI Transactions on Intelligent Systems
基金
National Natural Science Foundation of China(No.61170057,60875080)
关键词
数据挖掘
计算机技术
发展现状
人工智能
computer virus detection
artificial immune system
immune algorithms
hierarchical model
negative selection algorithm with penalty factor