Honeypot Allocation for Cyber Deception in Dynamic Tactical Networks: A Game Theoretic Approach

Sayed, Md Abu; Anwar, Ahmed H.; Kiekintveld, Christopher; Kamhoua, Charles

doi:10.1007/978-3-031-50670-3_10

Cited by 5 publications

(3 citation statements)

References 26 publications

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“…3. For this 20node network, the defender has 10 actions for honeypot allocations including (6,12), (5,11), (16,19), (11,15), (0,5), (16,20), (12,16), (0,6), (15,19), (15,18), while the attacker selects between 4 attack paths: path1 = [0, 5,11,15,18], path2 = [0, 5,11,15,19], path3 = [0, 6,12,16,19], path4 = [0, 6,12,16,20].…”

Section: Numerical Resultsmentioning

confidence: 99%

“…The synergies between game theory and machine learning to formulate defensive deception discussed in (Zhu et al 2021). A game-theoretic approach for strategically allocating honeypots in dynamic tactical networks to enhance cyber deception is presented in (Sayed et al 2023).…”

Section: Game Theoretic Deceptionmentioning

confidence: 99%

“…Securing tactical networks is challenging due to their mobile nature, rendering the defender's base policy ineffective and sub-optimal over time. Despite the increasing attention given to cyber deception in the past decade, the cyber-deception literature lacks regarding the incorporation of mobility features and anticipation of the future evolution of tactical networks (Sayed et al 2023). In this paper, we rely on dynamic attack graphs and game theory to model network mobility.…”

Section: Introductionmentioning

confidence: 99%

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Strategic Honeypot Allocation in Dynamic Networks: A Game-Theoretic Approach for Enhanced Cybersecurity

Sayed,

Hemida,

Kiekintveld

et al. 2024

Preprint

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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.

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Section: Numerical Resultsmentioning

confidence: 99%

Section: Game Theoretic Deceptionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Strategic Honeypot Allocation in Dynamic Networks: A Game-Theoretic Approach for Enhanced Cybersecurity

Sayed,

Hemida,

Kiekintveld

et al. 2024

Preprint

Self Cite

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Enhancing cloud security: harnessing bayesian game theory for a dynamic defense mechanism

Kandoussi,

Houmairi,

El Mir

et al. 2024

Cluster Comput

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Improving Quality of Service and HTTPS DDoS Detection in MEC Environment With a Cyber Deception-Based Architecture

Kabdjou,

Shinomiya

2024

IEEE Access

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Creating a cyber deception framework for 5G networks, particularly in IoT and cellular applications, is complex due to critical constraints in managing resources, meeting low latency demands, and addressing security concerns. While cloud computing aids in alleviating some limitations, it often falls short in meeting low-latency requirements. Multi-Access Edge Computing (MEC) has emerged as a solution by bringing resources closer to User Equipment (UEs) to reduce latency. Various MEC architectures have leveraged Software Defined Networking (SDN), Network Function Virtualization (NFV), Service Function Chaining (SFC), Network Slicing (NS), decision-making systems, and deception components. However, none have integrated these technologies comprehensively to achieve superior Quality of Service (QoS) and strengthen security. In this paper, we unify SDN, NFV, SFC, NS, decision-making technologies, and deception to efficiently manage MEC server resources and lure attackers. We utilize cyber deception metrics, including request collection rates over time and variations in request numbers concerning different botnet sizes. Moreover, we meticulously address QoS parameters such as latency, computing, storage, and bandwidth resources. Our approach initiates with a mathematical model for MEC server resource allocation, introducing a novel architecture that reduces bandwidth, computing, and storage resource usage. We introduce a cyber deception strategy utilizing uniform distribution and random selection to divert potential attackers. Simulations validate efficient resource management, notably reducing end-to-end latency for requests processed on the edge and in the cloud. This enhancement improves QoS within the MEC system and provides valuable insights for advancing decision-making technologies.

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Honeypot Allocation for Cyber Deception in Dynamic Tactical Networks: A Game Theoretic Approach

Cited by 5 publications

References 26 publications

Strategic Honeypot Allocation in Dynamic Networks: A Game-Theoretic Approach for Enhanced Cybersecurity

Strategic Honeypot Allocation in Dynamic Networks: A Game-Theoretic Approach for Enhanced Cybersecurity

Enhancing cloud security: harnessing bayesian game theory for a dynamic defense mechanism

Improving Quality of Service and HTTPS DDoS Detection in MEC Environment With a Cyber Deception-Based Architecture

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