Cognitive radio networks (CRNs) are threatened by smart jammers that aim to block the ongoing transmissions of secondary users according to their transmission patterns obtained from public control channels or compromised secondary users. Without requiring any pre-shared PHY-layer keys at the receivers, the uncoordinated frequency hopping (UFH) technique that was proposed to address smart jammers suffers from a low communication efficiency. In this paper, we develop a UFHbased collaborative broadcast system over universal software radio peripherals (USRPs), which exploits the node cooperation to improve the broadcast efficiency and jamming resistance of CRNs. Experiments are performed over USRPs to evaluate the broadcast performance against smart jammers under various network topologies. We investigate the impact of the CRN bandwidth, the prediction accuracy of smart jammers regarding the CRN frequency hopping pattern, and the jamming power and signal pattern. Experimental results show that the proposed broadcast system is more robust than three benchmark broadcast systems in most jamming scenarios.

In this paper, we propose a privacy-preserving proximity-based security system for location-based services in wireless networks, without requiring any pre-shared secret, trusted authority, or public key infrastructure. In this system, the proximity-based authentication and session key establishment are implemented based on spatial temporal location tags. Incorporating the unique physical features of the signals sent from multiple ambient radio sources, the location tags cannot be easily forged by attackers. More specifically, each radio client builds a public location tag according to the received signal strength indicators, sequence numbers, and media access control (MAC) addresses of the ambient packets. Each client also keeps a secret location tag that consists of the packet arrival time information to generate the session keys. As clients never disclose their secret location tags, this system is robust against eavesdroppers and spoofers outside the proximity range. The system improves the authentication accuracy by introducing a nonparametric Bayesian method called infinite Gaussian mixture model in the proximity test and provides flexible proximity range control by taking into account multiple physical-layer features of various ambient radio sources. Moreover, the session key establishment strategy significantly increases the key generation rate by exploiting the packet arrival time of the ambient signals. The authentication accuracy and key generation rate are evaluated via experiments using laptops in typical indoor environments.