Biblio

5G and beyond 5G low power wireless networks make Internet of Things (IoT) and Cyber-Physical Systems (CPS) applications capable of serving massive amounts of devices and machines. Due to the broadcast nature of wireless networks, it is crucial to secure the communication between these devices and machines from spoofing and interception attacks. This paper is concerned with the security of carrier frequency offset (CFO) based continuous physical layer authentication. The interaction between an attacker and a defender is modeled as a dynamic discrete leader-follower game with imperfect information. In the considered model, a legitimate user (Alice) communicates with the defender/operator (Bob) and is authorized by her CFO continuously. The attacker (Eve), by listening/eavesdropping the communication between Alice and Bob, tries to learn the CFO characteristics of Alice and aims to inject malicious packets to Bob by impersonating Alice. First, by showing that the optimal attacker strategy is a threshold policy, an optimization problem of the attacker with exponentially growing action space is reduced to a tractable integer optimization problem with a single parameter, then the corresponding defender cost is derived. Extensive simulations illustrate the characteristics of optimal strategies/utilities of the players depending on the actions, and show that the defender’s optimal false positive rate causes attack success probabilities to be in the order of 0.99. The results show the importance of the parameters while finding the balance between system security and efficiency.

Physical layer authentication (PLA) has recently been discussed in the context of URLLC due to its low complexity and low overhead. Nevertheless, these schemes also introduce additional sources of error through missed detections and false alarms. The trade-offs of these characteristics are strongly dependent on the deployment scenario as well as the processing architecture. Thus, considering a feature-based PLA scheme utilizing channel-state information at multiple distributed radio-heads, we study these trade-offs analytically. We model and analyze different scenarios of centralized and decentralized decision-making and decoding, as well as the impacts of a single-antenna attacker launching a Sybil attack. Based on stochastic network calculus, we provide worst-case performance bounds on the system-level delay for the considered distributed scenarios under a Sybil attack. Results show that the arrival-rate capacity for a given latency deadline is increased for the distributed scenarios. For a clustered sensor deployment, we find that the distributed approach provides 23% higher capacity when compared to the centralized scenario.