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Dynamic detection for computer virus based on immune system. (English) Zbl 1210.94091
Summary: Inspired by biological immune system, a new dynamic detection model for computer virus based on immune system is proposed. The quantitative description of the model is given. The problem of dynamic description for self and nonself in a computer virus immune system is solved, which reduces the size of self set. The new concept of dynamic tolerance, as well as the new mechanisms of gene evolution and gene coding for immature detectors is presented, improving the generating efficiency of mature detectors, reducing the false-negative and false-positive rates. Therefore, the difficult problem, in which the detector training cost is exponentially related to the size of self-set in a traditional computer immune system, is thus overcome. The theory analysis and experimental results show that the proposed model has better time efficiency and detecting ability than the classic model ARTIS.
MSC:
94A60Cryptography
68P25Data encryption
92B20General theory of neural networks (mathematical biology)
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