Game-Theoretic Analysis of Adaptive Behavior Between Attacker and Intrusion Detection System in IoT Gateways

Authors

  • Mojtaba Sandoughi Sandoughi * Department of Computer Engineering, Faculty of Electrical and Computer Engineering, University of Birjand, Birjand, Iran. https://orcid.org/0009-0008-2485-0639
  • Mohammad Malek Raeisi Department of Computer Engineering, Faculty of Electrical and Computer Engineering, University of Birjand, Birjand, Iran.
  • Hamid Saadatfar Department of Computer Engineering, Faculty of Electrical and Computer Engineering, University of Birjand, Birjand, Iran.

https://doi.org/10.48314/ijorai.v2i1.86

Abstract

With the rapid expansion of the Internet of Things (IoT) and the increasing dependence of smart infrastructures on communication gateways, securing these gateways against adaptive attacks has become a fundamental challenge in computer engineering. In many existing methods, the behavior of either the attacker or the Intrusion Detection System (IDS) is modeled statically or independently of the opponent's actions. However, in real-world scenarios, both sides continuously learn and adapt. In this study, a game-theoretic framework is proposed to analyze the adaptive behavior of an attacker and an IDS in IoT gateways. The interaction between the attacker and the IDS is modeled as a repeated game with memory-one strategies, and the mutual learning process is implemented using incremental optimization of each agent's long-term payoff. Furthermore, to adapt the model to the practical constraints of the IoT, the cost of processing resources and energy consumption of the IDS system is incorporated into its utility function. Numerical simulation results show that asymmetry in the learning speeds of the attacker and the IDS plays a decisive role in the stability of IoT gateway security. Specifically, when the IDS adapts at a faster rate than the attacker, the attacker's behavior is significantly suppressed, and the probability of successful attacks decreases, although the operational costs of the IDS increase. Conversely, for intermediate learning speeds, an adaptive competitive dynamic is observed in which neither party achieves a sustainable advantage. The results of this study can be utilized as an analytical tool for designing and tuning lightweight IDSs in IoT gateways.    

Keywords:

Internet of things, Intrusion detection system, Game theory, Adaptive learning, Network security

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Published

2026-03-18

Issue

Vol. 2 No. 1 (2026): International Journal of Operations Research and Artificial Intelligence (IJORAI)

Section

Articles

How to Cite

Sandoughi, M. S., Malek Raeisi, M. ., & Saadatfar, H. . (2026). Game-Theoretic Analysis of Adaptive Behavior Between Attacker and Intrusion Detection System in IoT Gateways. International Journal of Operations Research and Artificial Intelligence , 2(1), 31-41. https://doi.org/10.48314/ijorai.v2i1.86

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