Self-Nonself Discrimination in a Computer
SP '94 Proceedings of the 1994 IEEE Symposium on Security and Privacy
The effect of binary matching rules in negative selection
GECCO'03 Proceedings of the 2003 international conference on Genetic and evolutionary computation: PartI
An immune-based model for computer virus detection
CANS'05 Proceedings of the 4th international conference on Cryptology and Network Security
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A virus detection model based on artificial immune principles with real-valued negative selection (RVNS) is proposed. Feature vectors of program code are mapped into high dimension real-valued space. The architecture of this model, the formal definitions of self, nonself, antigen, antibody, and gene library are given. Then the process of self-tolerance of variable-sized detectors in real-valued space is discussed in detail. Variable-sized detectors provide concise representation of the detectors derived from benign files, which reduces the size of detectors set and advances the detection rate. The experimental results show that the model can detect obfuscated and firstly unknown virus more effectively than traditional model.