Visible to the public On the Tradeoff Between Privacy and Utility in Collaborative Intrusion Detection Systems-A Game Theoretical ApproachConflict Detection Enabled

TitleOn the Tradeoff Between Privacy and Utility in Collaborative Intrusion Detection Systems-A Game Theoretical Approach
Publication TypeConference Paper
Year of Publication2017
AuthorsJin, Richeng, He, Xiaofan, Dai, Huaiyu
Conference NameProceedings of the Hot Topics in Science of Security: Symposium and Bootcamp
PublisherACM
Conference LocationHanover, MD, USA
ISBN Number978-1-4503-5274-1
KeywordsCollaborative Intrusion Detection Systems, game theory, Utility-privacy tradeoff
Abstract

Intrusion Detection Systems (IDSs) are crucial security mechanisms widely deployed for critical network protection. However, conventional IDSs become incompetent due to the rapid growth in network size and the sophistication of large scale attacks. To mitigate this problem, Collaborative IDSs (CIDSs) have been proposed in literature. In CIDSs, a number of IDSs exchange their intrusion alerts and other relevant data so as to achieve better intrusion detection performance. Nevertheless, the required information exchange may result in privacy leakage, especially when these IDSs belong to different self-interested organizations. In order to obtain a quantitative understanding of the fundamental tradeoff between the intrusion detection accuracy and the organizations' privacy, a repeated two-layer single-leader multi-follower game is proposed in this work. Based on our game-theoretic analysis, we are able to derive the expected behaviors of both the attacker and the IDSs and obtain the utility-privacy tradeoff curve. In addition, the existence of Nash equilibrium (NE) is proved and an asynchronous dynamic update algorithm is proposed to compute the optimal collaboration strategies of IDSs. Finally, simulation results are shown to validate the analysis.

URLhttp://doi.acm.org/10.1145/3055305.3055311
DOI10.1145/3055305.3055311
Citation KeyJin:2017:TPU:3055305.3055311
Refereed DesignationRefereed

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