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《Mind and Computation》 2009-01
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Adaptive Web Intrusion Detection Based on Immune and Fuzzy Logic

WANG Jin-shui, ZHANG Dong-zhan, SHI Xiu-sheng, LAI Xing-rui (Computer Science Department, Xiamen University,Xiamen 361005, China)  
Web servers and web applications have become one of the most important communication channels on the Internet. Web-based vulnerabilities represent a substantial portion of the security exposures of computer networks. It appears more and more difficult to detect the web intrusion. This paper describes an adaptive web intrusion detection model based on immune and fuzzy logic. The model creates respectively the fuzzy rule collection of natural behaviour mode and inspecting behaviour mode with the improved generation of candidate itemsets. The web intrusion is detected by the difference between the two rule collections. Besides, the model updates fuzzy rules based on immune automatically and constantly to improve the ability of detecting new intrusions. Experiment results indicate that the model has better efficiency in identifying the abnormal intrusion compared with no update model and non-fuzzy model.
【Fund】: supported by the National Natural Science Foundation of China under Grant No.50604012~~
【CateGory Index】: TP393.08
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