[1]Roy, S., Ellis, C., Shiva, S., Dasgupta, D., Shandilya, V., & Wu, Q. (2010, January). A survey of game theory as applied to network security. In System Sciences (HICSS), 2010 43rd Hawaii International Conference on (pp. 1-10). IEEE.
[2]Manshaei, M. H., Zhu, Q., Alpcan, T., Bacşar, T., & Hubaux, J. P. (2013). Game theory meets network security and privacy. ACM Computing Surveys (CSUR), 45(3), 25.
These will provide the basic links to other papers on particular problems of game theory applied to IDS
A more specific topic is the subversion of learning algorithms in adversarial conditions (Typical applications are spam filters an IDSs). Some references are:
[3] Dalvi, N., Domingos, P., Mausam, Sanghai, S., & Verma, D. (2004). Adversarial classification. In Proceedings of the tenth acm sigkdd international conference on knowledge discovery and data mining (pp. 99–108). New York, NY, USA: ACM.
[4] Lowd, D., & Meek, C. (2005). Adversarial learning. In Proceedings of the eleventh ACM SIGKDD international conference on Knowledge discovery in data mining (pp. 641–647). New York, NY,
USA: ACM.
[5] Liu, W., & Chawla, S. (2009, December). A game theoretical model for adversarial learning. In Data Mining Workshops, 2009. ICDMW'09. IEEE International Conference on (pp. 25-30). IEEE.