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The Research And Design Of Intrusion Detection System Based On RBF Neural Network

Posted on:2011-01-07Degree:MasterType:Thesis
Country:ChinaCandidate:J Z ZhaoFull Text:PDF
GTID:2178360308958533Subject:Control theory and control engineering
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Network security has become the information age challenges facing humanity, the domestic network security issues become increasingly prominent. Specific performance: computer system by virus infection and damage is very serious; computer hacking has become a major threat; information infrastructure challenges facing network security; information systems in forecasting, response, prevention and recovery capabilities there are many weak links; frequent network of political subversion. If you do not solve these problems, the information will hinder the development process. Intrusion detection technology is an important dynamic security protection technology,Intrusion detection is a computer and network resources to identify malicious behavior and response process, it applies to the offensive strategy, in the case does not affect network performance, can detect the network, providing internal and external attacks and misuse in real-time monitoring. Recent years, as network and security technologies, the rapid development of new intrusion detection techniques have emerged, including: artificial neural networks, genetic algorithms, fuzzy data mining techniques. Which, based on artificial neural network intrusion detection technology is particularly important. Artificial neural networks to adaptive and learning from group better fault tolerance and parallelism advantages of associative memory and Lenovo being the world into attention in the field of intrusion detection has played an important role.This paper described the intrusion detection and artificial neural network concepts and related technologies, intrusion detection system status, through the analysis of current intrusion detection models using larger defect, a radial basis function (Radial Basic Functions) neural network intrusion detection system model, which overcomes the traditional rule-based intrusion detection systems library management problems. Has overcome the traditional system only determine whether the abnormal intrusion, intrusions are not identified which type of defect, so the system can achieve real-time monitoring of network and host state, to prevent the unpredictable nature of the invasion. The model has good ease of use and scalability, is a development of an effective means of safety management systems.Finally, we trained neural network between pairs of the detection experiment results show that the radial basis function neural network intrusion detection technology used to improve detection and effective De accuracy and performance of intrusion detection systems.Radial basis function of intrusion detection is a very active area of research. In this paper, given that some of the areas in the future need for research and better direction.
Keywords/Search Tags:Network security, intrusion detection systems, radial basis function, neural network
PDF Full Text Request
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