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Virus Detection Technology Based on Artificial Immune

Author: ChaiZuo
Tutor: ChengChunLing
School: Nanjing University of Posts and Telecommunications
Course: Applied Computer Technology
Keywords: Artificial Immune Virus Detection P2P networks Cloud Computing
CLC: TP393.08
Type: Master's thesis
Year: 2012
Downloads: 40
Quote: 0
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With the rapid development of computer network technology, network viruses are increasingly flooding the dangers of the virus has become one of the most serious threats in the field of computer security. P2P networks and cloud computing platforms, the large number of nodes interconnected together, as long as there is a node infected with the virus, the virus can easily spread quickly, and a threat to the safety of all nodes in the network computing environment. Traditional virus detection technologies unknown virus and less efficient, the new network environment has been unable to meet the demand for virus detection. Artificial immune theory is the analog of the biological immune system, with the precise identification of the characteristics of autologous and invasive alien and, therefore, it is necessary to study the new virus detection technology based on artificial immune. In this paper, the theory of artificial immune algorithm research, P2P networks and cloud computing platform virus detection research objectives, mainly made in the following three areas of work: (1) summary and analysis of the existing virus detection technology and current facing challenges, focuses on the concept of artificial immune theory, the current research status and its applications in computer virus detection. (2) P2P networks have the advantage of a convenient resource sharing and direct communication, but also for the spread of the virus, this paper, the characteristics of P2P networks, based collaboration immune virus detection model of P2P networks, peer nodes collaboration to achieve shared memory detector; generate the mature detectors for negative selection algorithm, there are a lot of redundancy, affecting the detection efficiency is proposed based on secondary mature negative selection algorithm; immune fusion and virus detection stage P2P network virus detection algorithm. Simulation results show that the algorithm effectively reducing the redundancy detector, improving the utilization efficiency of the detector. In the same time, the memory detector can be quickly share a node in the network, to improve the security of P2P network. (3) the use of cloud computing platform with powerful data processing capability characteristics, combined with the idea of ??artificial immune network evolution, virus detection model put forward an improved immune network cloud environment, and gives improved immune network virus detection algorithm based on MapReduce . Generated through the mature detector based on the gene pool in the construction phase of the immune network algorithm to generate the mature detector test set by the detector in the evolutionary stage of the introduction of fitness and stimulate the level of the test set to achieve the evolution of the collaboration between the detector and continuously optimize the detector in the immune network, and to improve the mature detector variability factor, in order to improve the efficiency of the evolution of the immune network, thereby enhancing the entire immune network cloud platform virus detection ability and detection efficiency. Simulation results show that the improved immune network algorithm have better detection performance can improve the entire cloud computing platform virus detection efficiency and safety.

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