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.

Honeypots play a crucial role in implementing various cyber deception techniques as they can mislead attackers and divert them away from valuable assets. The topology of tactical networks changes over time due to the topographical environment and node mobility. An impactful strategic placement of honeypots in tactical networks should essentially consider not only network aspects but also attackers' preferences. To this end, we propose a game-theoretic approach that models an attack-defense scenario and develops an optimal honeypot allocation strategy for the defender. Our approach takes into consideration the changes in network connectivity and the specific features and criticality of different nodes. In particular, we introduce a two-player dynamic game model that explicitly incorporates the future state evolution resulting from changes in 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 in terms of the reconfiguration cost of honeypot re-allocation due to mobility. We present an iterative algorithm to find Nash equilibrium strategies. Unfortunately, this class of games suffers from the curse of dimensionality due to the size of the large state space. Therefore, we evaluate the scalability of our algorithm and provide a compact state space that shows a significant reduction in terms of runtime. Finally, we relax the assumption that the defender has full up-to-date knowledge of the network topology. We present a sensitivity-analysis-based approach to quantify the impact of imperfect information in terms of the defender reward. We validate our approach numerically via extensive simulations, demonstrating that our game model successfully enhances network security and is more scalable.

In the evolving landscape of cybersecurity, the utilization of cyber deception has gained prominence as a proactive defense strategy against sophisticated attacks. This paper presents a comprehensive survey that investigates the crucial network requirements essential for the successful implementation of effective cyber deception techniques. With a focus on diverse network architectures and topologies, we delve into the intricate relationship between network characteristics and the deployment of deception mechanisms. This survey provides an in-depth analysis of prevailing cyber deception frameworks, highlighting their strengths and limitations in meeting the requirements for optimal efficacy. By synthesizing insights from both theoretical and practical perspectives, we contribute to a comprehensive understanding of the network prerequisites crucial for enabling robust and adaptable cyber deception strategies.