Optimal Sensing Disruption: A Generalized Framework for a Power-Limited Adversary

Abstract

A generalized framework of spectrum sensing disruption for a power-limited adversary is proposed in this paper. In the literature, a conventional sensing attack typically assumes that the adversary has perfect knowledge of the spectral usage status. The framework in this paper considers a more general case where there are uncertainties in the estimates at the adversary. These uncertainties are modeled utilizing the probability of detection and the probability of false alarm. Then, the sum of the conditional probabilities of false detection at the secondary within the spectral range of interest, conditioned on the adversary's estimated spectrum usage status, is maximized. It is shown that the optimal sensing attack, given perfect estimation is a special case of the proposed framework. When the adversary has perfect spectrum usage information, this framework reduces to a previously demonstrated optimal sensing disruption. When the adversary has imperfect information on the spectral status, the proposed framework is significantly more robust than conventional sensing attacks. Further, when the adversary's power budget increases, it asymptotically approaches the sensing disruption performance upper bound.

Adversarial Robustness in Cognitive Radio Networks

“…In [21], a secure and energy-efficient cooperative spectrum sensing scheme was newly proposed. In [22], a generalized framework for a power-limited adversary in terms of the optimal sensing disruption was theoretically proposed. In [23] and for the process of spectrum sensing, secure routing scenarios were deeply taken into account which was based mainly upon the nodes' behaviour.…”