Privacy-preserving aggregation for cooperative spectrum sensing

Abstract

Cognitive radio technology has been proposed as a promising way to alleviate spectrum scarcity. In cognitive radio networks, cooperative spectrum sensing is an effective approach to improve spectrum-estimation accuracy. In this approach, a fusion center (FC) outsources sensing tasks to secondary users (SUs), and aggregates sensing reports provided by SUs to estimate spectrum availability. However, as sensing reports are highly correlated to SUs’ real locations, revealing sensing reports to an untrusted FC may incur a serious privacy threat for SUs. In this paper, we propose an efficient scheme that allows the FC to learn desired statistics from a group of SUs without compromising individual privacy. Moreover, the FC is still able to compute the sum over the remaining SUs when some SUs fail to submit their reports. Besides, to ensure secure communication in cooperative spectrum sensing, the proposed scheme verifies the legitimacy of SUs by utilizing the elliptic curve cryptography technique. The results of security analysis show that the proposed scheme achieves the combined objectives of privacy preservation, authentication, fault tolerance, and resistance to various types of attacks. Performance evaluation results demonstrate the feasibility and practicality of the proposed scheme.