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Anup K Ghosh, Aaron Schwartzbard. A study in using neuralnetworks for anomaly and misuse detection. The 8th USENIX Security Symposium, Washington D C, 1999: 46-57.[2]Balajinath B, Raghavan S V. Intrusion detection through learning behavior model[J].Computer Communications.2001, 24(12):1202-1212[3]Jha S, Tan K, Maxion R A. Markov Chains, classifiers and intrusion detection. The 14th IEEE Computer Security Foundations Workshop, Canada, 2001: 206-215.[4]張箭, 龔儉. 一種基于模糊綜合評(píng)判的入侵異常檢測(cè)方法. 計(jì)算機(jī)研究與發(fā)展, 2003, 40(6): 776-782.[5]Fisher R A. The statistical utilization of multiple measurements. Annals of Eugenics, 1938, 6(8): 376-386.[6]Wilson D, Martinez R. Improved heterogeneous distance functions. Journal of Artificial Intelligence Research, 1997, 6(1): 1-34.[7]Lee W, Stolfo SJ. A data mining framework for building intrusion detection medel, In: Gorgl, Keiter M K, eds. Proceedings of He 1999 IEEE Symposium on Security and Privacy, Oakland, CA, IEEE Computer Society Press, 1999: 120-132.[8]Forrest S, Hofmeyr S A, et al.. A sense of self for unix process. In: Proceedings of 1996 IEEE Symposium on Computer Security and Privacy, Canada, 1996: 120-128.[9]Lee W, Stolfo S, Chan P. Learning patterns from unix process execution traces for intrusion detection. In: Proceeding of AAAI Workshop: AI Approaches to Fraud Detection and Risk Management, Washington D C, 1997: 191-197.
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