Title

Reinforcement learning assisted impersonation attack detection in device-to-device communications

Document Type

Journal Article

Publication Title

IEEE Transactions on Vehicular Technology

Publisher

IEEE

School

Centre for Communications and Electronics Research / School of Engineering

Comments

Tu, S., Waqas, M., Rehman, S. U., Mir, T., Abbas, G., Abbas, Z. H., ... Ahmad, I. (2021). Reinforcement learning assisted impersonation attack detection in device-to-device communications. IEEE Transactions on Vehicular Technology. Advance online publication. https://doi.org/10.1109/TVT.2021.3053015

Abstract

IEEE In device-to-device (D2D) communications, the channel gain between a transmitter and a receiver is difficult to predict due to channel variations. Hence, an attacker can easily perform an impersonation attack between two authentic D2D users. As a countermeasure, we propose a reinforcement learning-based technique that guarantees identification of the impersonator based on channel gains. To show the merit of our technique, we report its performance in terms of false alarm rate, miss-detection rate, and average error rate. The secret key generation rate is also determined under the impersonation attack based on physical layer security.

DOI

10.1109/TVT.2021.3053015

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