An Application-Layer Distributed Intrusion Detection Model Based on the C/S Mode

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Abstract:

In order to overcome the disadvantages of the traditional distributed intrusion detection system, an application-layer distributed intrusion detection model based on the C/S mode is proposed here. The new model, is composed of a main system of server and several sub-systems of clients, fully utilizes detection abilities of the client by means of computing the belief dynamically, while the cost is not increased. Theoretical analysis and experimental results show that the model is a simple structure, reasonable design and higher accuracy than the traditional models.

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882-886

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September 2012

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[1] Hu Changzhen, Network intrusion detection theory and technology, first ed, Beijing institute oftechnology press, (2006).

Google Scholar

[2] Chimphlee W, Abdullah A H. To Detect Misuse and Anomaly Attacks Through Rule Induction Analysis and Fuzzy Methods[J]. WSEAS Trans on Computers, 2006, 5(1): 49-54.

Google Scholar

[3] Huang Guoyan, Chang Xuliang, Gao Jianpei. Application research of fuzzy logic theory in intrusion detection systems[J]. Engineering and applications. 2010, 46(98): 110-113.

Google Scholar

[4] Tong X J, Wang Z, Yn H N. A research using hybrid RBF/Elman neural networks for intrusion detection system secure model[J]. Computer physics Communications. 2009, 180(10): 1795-1801.

DOI: 10.1016/j.cpc.2009.05.004

Google Scholar

[5] Xu qinzhen, Yangluxi. An optimized neural network tree based on anomaly intrusion detection method[J]. Signal processing. 2010, 26(11): 1663-1669.

Google Scholar

[6] D. Dasgupta, F. Gonzalez.An Immunity-based Technique to Characterize Intrusions In Computer Networks[J]. IEEE Transactions on Evolutionary Computation, 2005, 6(3): 281~291.

DOI: 10.1109/tevc.2002.1011541

Google Scholar

[7] Yu Yan, Huang Hao. An ensemble approach to intrusion detection based on improved multi-objective genetic algorithm. Journal of software. 2007,18(6):1369-1378.

DOI: 10.1360/jos181369

Google Scholar

[8] Fu Desheng, Zhou Shu, Guo Ping. Design and Implementation of distributed network intrusion detection system based on date mining. Computer science. 2009, 26(3):103-105.

Google Scholar