Citation

Ibrahim, Khalid and Malik, Aqdas Naveed and Waseem, Athar and Roslee, Mardeni and Ahmed, Sadiq (2024) Game-Theoretic Frameworks for Anti-Jamming in Cognitive Radio Networks: Advancements and Strategies. In: 2024 Multimedia University Engineering Conference (MECON), 23-25 July 2024, Cyberjaya, Malaysia.

Text Game-Theoretic Frameworks for Anti-Jamming in Cognitive Radio Networks_ Advancements and Strategies.pdf - Published Version Restricted to Repository staff only Download (294kB)

Abstract

This paper presents a comprehensive survey of stateof-the-art anti-jamming techniques applied in cognitive radio networks (CRNs) to counter jamming attacks. The study encompasses a comparative analysis of existing literature, evaluating various aspects such as game types, jammer characteristics, equilibrium concepts, and anti-jamming defense modes. Additionally, we conducted an in-depth review of reinforcement learning-based approaches, game-theoretic techniques, and various equilibrium concepts employed in CRN anti-jamming strategies. Moreover, the study highlights the effectiveness of deception mechanisms, including cover fire, honey pot, honey net, backscattering, and energy harvesting techniques in thwarting jamming attempts. By synthesizing the findings, this research provides a thorough understanding of defense techniques and their taxonomy in the context of CRNs. Furthermore, the study outlines future research directions and identifies potential loopholes in CRN security, offering valuable insights to guide further investigations in this critical domain. As the threats to CRNs persist and evolve, the insights gained from this survey contribute to the advancement of robust and secure CRN architectures, ultimately enhancing network resilience and reliability.

Item Type:	Conference or Workshop Item (Paper)
Uncontrolled Keywords:	Cognitive Radio Network
Subjects:	T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK5101-6720 Telecommunication. Including telegraphy, telephone, radio, radar, television
Divisions:	Faculty of Engineering (FOE)
Depositing User:	Ms Nurul Iqtiani Ahmad
Date Deposited:	07 Feb 2025 03:10
Last Modified:	07 Feb 2025 03:10
URII:	http://shdl.mmu.edu.my/id/eprint/13401

Downloads

Edit (login required)