Exploiting Spectrum Sensing Data for Key Management

In cognitive radio networks, secondary users (SUs) communicate on unused spectrum slots in the frequency bands assigned to primary users (PUs). Like any other wireless communication system, cognitive radio networks are ex- posed to physical layer attacks. In particular, we focus on two common at- tacks, namely, spectrum sensing data falsification and eavesdropping. Such attacks can be counteracted by using symmetric key algorithms, which how- ever require a complex key management scheme. In this paper we propose a novel algorithm that significantly reduces the complexity of the management of symmetric link keys by leveraging spectrum sensing data that is available to all nodes. In our algorithm, it is assumed that a primary secret key is pre-distributed to the legitimate SUs, which is needed every number of de- tection cycles. With the aid of the information provided in the primary key, our algorithm manipulates the collected samples so that a segment of the estimated sensing statistic at the two legitimate SUs can be used as a seed to generate a common symmetric link key. The link key is then employed to encrypt the transmitted data. Our algorithm exhibits very good performance in terms of bit mismatch rate (BMR) between two link keys generated at the two legitimate SUs. In addition, our solution is robust against the difference in the received signal to noise ratio between two legitimate SUs thus making it suitable for practical scenarios. Furthermore, our algorithm exploits the decision statistic that SUs use for spectrum sensing, hence, it does require neither extra processing nor extra time, allowing the SUs to quickly and securely tab into empty spectrum slots.