access icon free Rollout algorithm for light-weight physical-layer authentication in cognitive radio networks

© The Institution of Engineering and Technology
Received 01/12/2019, Accepted 26/05/2020, Revised 05/05/2020, Published 22/06/2020

Cognitive radio networks (CRNs) are vulnerable to spoofing attacks due to their wireless and cognitive nature. Since the traditional cryptographic authentication can hardly prevent such attacks in CRNs, the physical-layer authentication has been investigated for recent years. To achieve a light-weight physical-layer authentication, a rollout partially observable Markov decision process-based algorithm, named RoPOMDP, is proposed in this study. In general, RoPOMDP formulates the physical-layer authentication as a zero-sum game, based on which a hypothesis test upon channel vectors is developed. That allows us to design the gains for both spoofers and receivers based on Bayesian risks for the game, in which the spoofing attack probability is predicted by a non-linear function approximation utilising v-support vector regression. Then, a RoPOMDP is employed to estimate the optimal threshold for the test statistic such that spoofing attacks can be detected. The theoretical analysis and simulations indicate that: (i) RoPOMDP improves the spoofing detection accuracy; (ii) as a light-weight algorithm, the complexity of RoPOMDP is lower than contemporary ones.

Inspec keywords: authorisation; Markov processes; cognitive radio; function approximation; Bayes methods; telecommunication security; regression analysis

Other keywords: rollout algorithm; light-weight physical-layer authentication; v-support vector regression; cryptographic authentication; CRNs; wireless nature; cognitive radio networks; nonlinear function approximation; Markov decision process-based algorithm; spoofing attack probability; RoPOMDP; cognitive nature

Subjects: Radio links and equipment; Markov processes; Data security; Markov processes; Interpolation and function approximation (numerical analysis); Interpolation and function approximation (numerical analysis)

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