The Research Of Computer Virus Detection Technology Based On A New Negative Algorithm

Computer virus detection system is a network security system to be used to detect threats or hazards to the host and the computer network code, Biological immune system is a mechanism to protect living organisms from harmful external pathogens, which has distributed parallel processing, self-organization, immune memory and robustness properties, Traditional computer virus detection technology is a passive defense technology, based on the immune system and computer virus detection system similarity, So we learn from the immune system theory to improve virus detection performance.This paper analyses the problems of the traditional negative selection algorithm, and introduced improvement and effort in these areas, Based on a cutting space negative selection algorithm, proposes a kind of a new cut negative selection algorithm which is used to detecting the binary string, this algorithm can eliminate redundant detectors, reduce the detector vulnerability, but also to some extent prevent the black hole; we also introduce the principles of the tree-level management system and tabu search strategy, this paper presents a new taboo artificial immune network algorithm which combinations of the tabu search algorithm and the artificial immune algorithm combines, to improve the detection search speed, update efficiency, saving the memory, this algorithm can achieve optimal global convergence; Finally, we analyses the selected data sets which selected from KDDCUP99 and tests show that the new negative selection algorithm has a higher detection efficiency, accuracy of detection and search speed, The main work of this paper is as follows,1) This paper analyzes the problems of the traditional negative selection and the computer virus detection technology, and concluded the improvements and implementation methods in the areas.2) According to the cutting space negative selection algorithm, we presents a new cutting negative selection algorithm (CNSA) which is applied to the binary string detector generates, this algorithm improves detector effectively reduce the detection loopholes, and eliminate the redundant detectors, reduce the existence of black holes detector, the system only a small number of selfsets can detect a more comprehensive non-self-detector.3) Based on the combination of the tree-level model and the tabu search algorithm, we design a new kind of taboo artificial immune network algorithm, By setting the threshold T, the detectors can transform between tables which are the taboo table, the memory table and the evolutionary table, According to the sort of the detector affinity, which can inhibit the number of detectors to improve the detector efficiency and reduce the effective memory utilization.4) Screening the data sets, analyzing data, we can select data to validate the algorithm, and finally the paper design a new computer virus detection system based on the cutting negative selection algorithm, and analyzes the performance of the model.