The emerging paradigm for dynamic spectrum sharing is based on allowing secondary users (SUs) to exploit white space frequency that is not occupied by primary users. White space database provides an opportunity for SUs to obtain spectrum availability information by submitting a location-based query. However, this new paradigm can also be exploited by the attackers to significantly enhance their jamming capability due to the available channel information from spectrum queries, which is expected to increasingly block SUs. The challenge is that the unique characteristics (e.g., lack of the wide range frequencies or continuous broadband) make existing anti-jamming techniques (e.g., direct-sequence spread spectrum and frequency hopping spread spectrum) difficult to be applied. In this paper, we present a novel Jammer Inference-based Jamming Defense (jDefender) framework. The main idea of jDefender is inferring the likelihood of a user being a jammer based on the observed jamming events and then utilizing the inferred attack likelihood to enhance the effectiveness of a series of the proposed anti-jamming strategies. Specifically, we first propose the Channel Allocation-based Jammer Inference scheme to infer the likelihood of an SU being a jammer based on the channels occupied by SUs even under the collusion attack performed by multiple jammers. The strength of the anti-jamming strategies (e.g., puzzle difficulties, available spectrum resources) will be correlated with the possibility of an SU being a jammer to achieve the tradeoff between system performance and jamming tolerance. We then implement the proposed scheme on Universal Software Radio Peripheral and PC. Extensive evaluations are performed to validate the effectiveness of the attacks and countermeasures.

Database-driven Cognitive Radio Network (CRN) has been proposed to replace the requirement of spectrum sensing of terminal devices so that the operation of users is simplified. However, location privacy issues introduce a big challenge for securing database-driven CRN due to spectrum availability information. The existing works consider either PU or SU's location privacy while not the both. In this study, we identify a unified attack framework in which a curious user could infer a target's location based on the spectrum availability/utilization information. Further, we propose a location privacy protection mechanism, which allows both SU and PU to protect their location privacy by adopting a series of countermeasures. The location privacy and spectrum utility are the trade-off. In the countermeasures of location privacy preserving spectrum query process, both SU and database aim to maximize the location privacy with constraints of spectrum utility. Thus, they can obtain higher location privacy level with sacrifice of spectrum utility as long as the spectrum utility meets the requirements. We evaluate the unified attack and defence approaches based on simulation and demonstrate the effectiveness of the proposed location privacy preserving approaches.