Entice to Trap: Enhanced Protection against a Rate-Aware Intelligent Jammer in Cognitive Radio Networks

Khalid Ibrahim, Abdullah M. Alnajim, Aqdas Naveed Malik, Athar Waseem, Saleh Alyahya, Muhammad Islam and Sheroz Khan
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Khalid Ibrahim: Department of Electrical Engineering, Faculty of Engineering and Technology, International Islamic University, Islamabad 44000, Pakistan
Abdullah M. Alnajim: Department of Information Technology, College of Computer, Qassim University, Buraydah 51452, Saudi Arabia
Aqdas Naveed Malik: Department of Electrical Engineering, Faculty of Engineering and Technology, International Islamic University, Islamabad 44000, Pakistan
Athar Waseem: Department of Electrical Engineering, Faculty of Engineering and Technology, International Islamic University, Islamabad 44000, Pakistan
Saleh Alyahya: Department of Electrical Engineering, College of Engineering and Information Technology, Onaizah 2053, Saudi Arabia
Muhammad Islam: Department of Electrical Engineering, College of Engineering and Information Technology, Onaizah 2053, Saudi Arabia
Sheroz Khan: Department of Electrical Engineering, College of Engineering and Information Technology, Onaizah 2053, Saudi Arabia

Sustainability, 2022, vol. 14, issue 5, 1-20

Abstract: Anti-jamming in cognitive radio networks (CRN) is mainly accomplished using machine learning techniques in the domains of frequency, coding, power and rate. Jamming is a major threat to CRN because it can cause severe performance damage such as network isolation, network application interruption and even physical damage to infrastructure simple radio devices. With the improvement in communication technologies, the capabilities of adversaries are also increased. The intelligent jammer knows the rate at which users transmit data, which is based on the attractiveness factor of each user. The higher the data rate for a secondary user, the more attractive it is to the rate-aware jammer. In this paper, we present a dummy user in the network as a honeypot of the jammer to get the jammer’s attention. A new anti-jamming deceiving theoretical method based on rate modifications is introduced to increase the bandwidth efficiency of the entire cognitive radio-based communication system. We employ a defensive anti-jamming deception mechanism of the Pseudo Secondary User (PSU) to as an entice to trap the attacker by providing thus enhanced protection for the rest of the network from the impact of the attacker. Our analytical simulation results show a significant improvement in performance using the proposed solution. The utility of the proposed intelligent anti-jamming algorithm lies in its applications to support the secondary wireless sensor nodes.

Keywords: cognitive radio networks; anti-jamming; deception; stochastic game; pseudo secondary user; rate-aware jammers; cybersecurity (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
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