714 research outputs found
Honeypot Allocation for Cyber Deception in Dynamic Tactical Networks: A Game Theoretic Approach
Honeypots play a crucial role in implementing various cyber deception
techniques as they possess the capability to divert attackers away from
valuable assets. Careful strategic placement of honeypots in networks should
consider not only network aspects but also attackers' preferences. The
allocation of honeypots in tactical networks under network mobility is of great
interest. To achieve this objective, we present a game-theoretic approach that
generates optimal honeypot allocation strategies within an attack/defense
scenario. Our proposed approach takes into consideration the changes in network
connectivity. In particular, we introduce a two-player dynamic game model that
explicitly incorporates the future state evolution resulting from changes in
network connectivity. The defender's objective is twofold: to maximize the
likelihood of the attacker hitting a honeypot and to minimize the cost
associated with deception and reconfiguration due to changes in network
topology. We present an iterative algorithm to find Nash equilibrium strategies
and analyze the scalability of the algorithm. Finally, we validate our approach
and present numerical results based on simulations, demonstrating that our game
model successfully enhances network security. Additionally, we have proposed
additional enhancements to improve the scalability of the proposed approach.Comment: This paper accepted in 14th International Conference on Decision and
Game Theory for Security, GameSec 202
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