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Overview:

This paper proposes and investigates a game-theoretic approach to the malware filtering and detector placement problem which arises in network security. Their main objective is to develop optimal detector algorithms taking into account attacker strategies and actions. Assuming rational and intelligent attackers, they present a two-person zero-sum non-cooperative Markov security game framework as a basis for modeling the interaction between the attackers who generate malware traffic on a network and a corresponding Intrusion Detection System (IDS). Thus, they establish a formal model of the detector placement problem based on game theory and derive optimal strategies for both players. In addition, they test the strategies obtained in a realistic agent-based network simulation environment and compare the results of static and dynamic placement scenarios.

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Format:PDFSize:303 KB
Date:Aug 2007
Pages:17

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