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An evolutionary multi-agent approach to anomaly detection and cyber defense

Published: 12 October 2011 Publication History
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References

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Snort. http://www.snort.org/.
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S. Axelsson. Intrusion detection systems: A survey and taxonomy. 2000.
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S. Axelsson. The base-rate fallacy and the difficulty of intrusion detection. ACM Transactions on Information and System Security (TISSEC), 3(3):186-205, 2000.
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M. Carvalho and C. M. Teng. Automatic discovery of attack messages and pre- and postconditions automatic discovery of attack messages and pre- and post-conditions for attack graph generation. In E. L. Armistead, editor, 5th International Conference on Information Warfare and Security (ICIW), pages 378-388, Wright-Patterson AFB, Ohio, USA, April 8-9 2010. AFRL, Academic Publishing Limited.
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J. Hartigan and M. Wong. A k-means clustering algorithm. JR Stat. Soc., Ser. C, 28:100-108, 1979.
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D. Kim, H. Nguyen, and J. Park. Genetic algorithm to improve SVM based network intrusion detection system. In Advanced Information Networking and Applications, 2005. AINA 2005. 19th International Conference on, volume 2, pages 155-158. IEEE, 2005.
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C. Kruegel, D. Mutz, W. Robertson, and F. Valeur. Bayesian event classification for intrusion detection. 2003.
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A. Lazarevic, L. Ertoz, V. Kumar, A. Ozgur, and J. Srivastava. A comparative study of anomaly detection schemes in network intrusion detection. In Proceedings of the Third SIAM International Conference on Data Mining, volume 3, 2003.
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R. Lippmann, J. Haines, D. Fried, J. Korba, and K. Das. The 1999 DARPA off-line intrusion detection evaluation. Computer Networks, 34(4):579-595, 2000.
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J. McHugh. Testing intrusion detection systems: A critique of the 1998 and 1999 DARPA intrusion detection system evaluations as performed by lincoln laboratory. ACM Transactions on Information and System Security, 3(4):262-294, 2000.
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S. Mukkamala, G. Janoski, and A. Sung. Intrusion detection using neural networks and support vector machines. In Proceedings of IEEE international joint conference on neural networks, volume 1702, 2002.
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S. Patton, W. Yurcik, and D. Doss. An Achilles' heel in signature-based IDS: Squealing false positives in SNORT. In Proceedings of RAID 2001 fourth International Symposium on Recent Advances in Intrusion Detection October, volume 10, page 12. Citeseer, 2001.
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L. Portnoy, E. Eskin, and S. Stolfo. Intrusion detection with unlabeled data using clustering. In Proceedings of ACM CSS Workshop on Data Mining Applied to Security, Philadelphia, PA, 2001.
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Y. Qiao, X. Xin, Y. Bin, and S. Ge. Anomaly intrusion detection method based on HMM. Electronics Letters, 38(13):663-664, 2002.
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G. Schwarz. Estimating the dimension of a model. The annals of statistics, 6(2):461-464, 1978.

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CSIIRW '11: Proceedings of the Seventh Annual Workshop on Cyber Security and Information Intelligence Research
October 2011
18 pages
ISBN:9781450309455
DOI:10.1145/2179298
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 12 October 2011

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