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Virus detection method based on collaborative immune network evolutionary algorithm

An immune network, virus detection technology, applied in computing, computer security devices, instruments, etc., can solve the problems of reducing redundancy, slow execution speed, large amount of calculation, etc., to reduce the cost of calculation and improve the generation efficiency. Effect

Inactive Publication Date: 2012-10-24
NANJING UNIV OF POSTS & TELECOMM
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AI Technical Summary

Problems solved by technology

However, the aiNet immune network model has problems such as over-reliance on network suppression to reduce redundancy, large amount of calculation, and slow execution speed.

Method used

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  • Virus detection method based on collaborative immune network evolutionary algorithm
  • Virus detection method based on collaborative immune network evolutionary algorithm
  • Virus detection method based on collaborative immune network evolutionary algorithm

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specific Embodiment approach

[0076] (1) The initialization of the immune network includes the following steps:

[0077] Step 1.1) Node Pc1 extracts feature codes from M normal executable files, and then arranges and combines them to obtain a set of strings with a length of m bits as the self set. Non-self uses m-bit virus feature codes, and each m-bit character The string is a virus signature code, select T known virus signature codes in the network to form the initial non-self set, split the non-self set element information into gene fragments of equal length s, and add the obtained gene fragments to the gene pool; M, T, m, s can be selected according to actual needs;

[0078] Step 1.2) Select the gene fragments in the gene bank and randomly combine them into immature detectors with a length of m bits, and the multiple immature detectors generated by the combination form an immature detector set;

[0079] Step 1.3) Perform tolerance training on the initial immature detector set generated by the gene ban...

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Abstract

The invention discloses a virus detection method based on a collaborative immune network evolutionary algorithm, and belongs to the technical field of network security. According to the method, detectors in the immune network are optimized continually through the mutual collaboration among various immune cells. The method introducing a non-self set in the evolutionary process, and performing clonal selection on mature detectors based on the detector fitness to the non-self set; simultaneously, updating mutation methods with mutation step size self-adaptation and capable of changing mature detectors through an evolutionary algebra through the evolutionary algebra, and raising a network inhibition strategy based on concentration partition, thus, the network cell diversity is improved, and the redundancy rate of detectors is reduced simultaneously. According to the virus detection method based on the collaborative immune network evolutionary algorithm, advantages of the evolutionary algorithm and the artificial immune technology are combined and fully used, and the network virus detection efficiency is improved.

Description

technical field [0001] The invention relates to a virus detection method, in particular to a virus detection method based on a cooperative immune network evolution algorithm, which belongs to the cross-technical application field of computer network, information security and artificial immune system. Background technique [0002] The development of computer viruses, especially deformed viruses and network viruses, makes it more and more difficult for anti-virus researchers to find a method of preventing and controlling viruses that can meet people's needs. The study of artificial immunity has brought some inspiration to people. Because in the face of a large number of deformed viruses, the research on preventing and controlling computer viruses has fallen into a basic problem of how to make the computer system identify which are system applications ("self") and which are viruses ("non-self"). The biological immune system is a complex system composed of organs, cells and mol...

Claims

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Application Information

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IPC IPC(8): G06F21/22
Inventor 程春玲柴倩张登银张少娴
Owner NANJING UNIV OF POSTS & TELECOMM
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