A Reinforcement Learning Approach for Host-Based Intrusion Detection Using Sequences of System Calls-Reference-Cited by-同舟云学术

A Reinforcement Learning Approach for Host-Based Intrusion Detection Using Sequences of System Calls

Published:2005 Issue: Volume: Page:995-1003
ISSN:0302-9743
Container-title:Lecture Notes in Computer Science
language:
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Author:

Xu Xin,Xie Tao

Publisher

Springer Berlin Heidelberg

Link

http://link.springer.com/content/pdf/10.1007/11538059_103.pdf

Reference12 articles.

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2. Lee, W.K., Stolfo, S.J.: A Data Mining Framework for Building Intrusion Detection Model. In: Gong, L., Reiter, M.K. (eds.) Proceedings of the IEEE Symposium on Security and Privacy, pp. 120–132. IEEE Computer Society Press, Oakland (1999)

3. Mukkamala, S., Janoski, G., Sung, A.H.: Intrusion Detection Using Neural Networks and Support Vector Machines. In: Proceedings of IEEE International Joint Conference on Neural Networks, pp. 1702–1707 (2002)

4. Ryan, J., Lin, M.-J., Miikkulainen, R.: Intrusion Detection with Neural Networks. In: Advances in Neural Information Processing Systems, vol. 10. MIT Press, Cambridge (1998)

5. Lane, T., Brodley, C.: Temporal Sequence Learning and Data Reduction for Anomaly Detection. ACM Transactions on Information and System Security 2(3), 295–331 (1999)

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