Abstract
This paper investigates how intrusion detection system (IDS) sensors should best be placed on a network when there are several competing evaluation criteria. This is a computationally difficult problem and we show how Multi-Objective Genetic Algorithms provide an excellent means of searching for optimal placements.
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References
Goldberg, D.E.: Genetic Algorithms in Search, Optimization and Machine Learning. Addison-Wesley Longman Publishing Co., Inc., Boston (1989)
Coello, C.A.C., Nacional, L.: An updated survey of ga-based multiobjective optimization techniques. ACM Computing Surveys 32, 109–143 (1998)
Lu, W., Traore, I.: Detecting new forms of network intrusion using genetic programming. In: Proceedings of the 2003 Congress on Evolutionary Computation (2003)
Noel, S., Jajodia, S.: Attack graphs for sensor placement, alert prioritization, and attack response. In: Cyberspace Research Workshop (2007)
Rolando, M., Rossi, M., Sanarico, N., Mandrioli, D.: A formal approach to sensor placement and configuration in a network intrusion detection system. In: SESS 2006: Proceedings of the 2006 international workshop on Software engineering for secure systems, pp. 65–71. ACM, New York (2006)
Issariyakul, T., Hossain, E.: An Introduction to Network Simulator Ns2. Springer, Heidelberg (2008)
Shaikh, S.A., Chivers, H., Nobles, P., Clark, J.A., Chen, H.: Network reconnaissance. Network Security 11, 12–16 (2008)
Gu, G., Fogla, P., Dagon, D., Lee, W., Skoric, B.: Measuring intrusion detection capability: an information-theoretic approach. In: ASIACCS 2006: Proceedings of the 2006 ACM Symposium on Information, computer and communications security, pp. 90–101. ACM, New York (2006)
Luke, S.: A java-based evolutionary computation research system (2008), http://cs.gmu.edu/~eclab/projects/ecj/
Zitzler, E., Laumanns, M., Thiele, L.: Spea2: Improving the strength pareto evolutionary algorithm. Technical Report 103, Swiss Federal Institute of Technology (2001)
Shaikh, S.A., Chivers, H., Nobles, P., Clark, J.A., Chen, H.: A deployment value model for intrusion detection sensors. In: 3rd International Conference on Information Security and Assurance. LNCS, vol. 5576, pp. 250–259. Springer, Heidelberg (2009)
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Chen, H., Clark, J.A., Tapiador, J.E., Shaikh, S.A., Chivers, H., Nobles, P. (2009). A Multi-objective Optimisation Approach to IDS Sensor Placement. In: Herrero, Á., Gastaldo, P., Zunino, R., Corchado, E. (eds) Computational Intelligence in Security for Information Systems. Advances in Intelligent and Soft Computing, vol 63. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04091-7_13
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DOI: https://doi.org/10.1007/978-3-642-04091-7_13
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-04090-0
Online ISBN: 978-3-642-04091-7
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