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Dynamic detection for computer virus based on immune system

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Abstract

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.

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Correspondence to Tao Li.

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Supported by the National Natural Science Foundation of China (Grant No. 60573130), and the 863 Project of China (Grant No. 2006AA01Z435)

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Li, T. Dynamic detection for computer virus based on immune system. Sci. China Ser. F-Inf. Sci. 51, 1475–1486 (2008). https://doi.org/10.1007/s11432-008-0125-y

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  • DOI: https://doi.org/10.1007/s11432-008-0125-y

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