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.

Current physical layer authentication (PLA) mechanisms are mostly designed for static communications, and the accuracy degrades significantly when used in dynamic scenarios, where the network environments and wireless channels change frequently. To improve the authentication performance, it is necessary to update the hypothesis test models and parameters in time, which however brings high computational complexity and authentication delay. In this paper, we propose a lightweight cross-layer authentication scheme for dynamic communication scenarios. We use multiple characteristics based PLA to guarantee the reliability and accuracy of authentication, and propose an upper layer assisted method to ensure the performance stability. Specifically, upper layer authentication (ULA) helps to update the PLA models and parameters. By properly choosing the period of triggering ULA, a balance between complexity and performance can be easily obtained. Simulation results show that our scheme can achieve pretty good authentication performance with reduced complexity.

A novel physical layer authentication scheme is proposed in this paper by exploiting the time-varying carrier frequency offset (CFO) associated with each pair of wireless communications devices. In realistic scenarios, radio frequency oscillators in each transmitter-and-receiver pair always present device-dependent biases to the nominal oscillating frequency. The combination of these biases and mobility-induced Doppler shift, characterized as a time-varying CFO, can be used as a radiometric signature for wireless device authentication. In the proposed authentication scheme, the variable CFO values at different communication times are first estimated. Kalman filtering is then employed to predict the current value by tracking the past CFO variation, which is modeled as an autoregressive random process. To achieve the proposed authentication, the current CFO estimate is compared with the Kalman predicted CFO using hypothesis testing to determine whether the signal has followed a consistent CFO pattern. An adaptive CFO variation threshold is derived for device discrimination according to the signal-to-noise ratio and the Kalman prediction error. In addition, a software-defined radio (SDR) based prototype platform has been developed to validate the feasibility of using CFO for authentication. Simulation results further confirm the effectiveness of the proposed scheme in multipath fading channels.
 

Physical-layer authentication techniques exploit the unique properties of the wireless medium to enhance traditional higher-level authentication procedures. We propose to reduce the higher-level authentication overhead by using a state-of-the-art multi-target tracking technique based on Gaussian processes. The proposed technique has the additional advantage that it is capable of automatically learning the dynamics of the trusted user's channel response and the time-frequency fingerprint of intruders. Numerical simulations show very low intrusion rates, and an experimental validation using a wireless test bed with programmable radios demonstrates the technique's effectiveness.

Physical-layer authentication techniques exploit the unique properties of the wireless medium to enhance traditional higher-level authentication procedures. We propose to reduce the higher-level authentication overhead by using a state-of-the-art multi-target tracking technique based on Gaussian processes. The proposed technique has the additional advantage that it is capable of automatically learning the dynamics of the trusted user's channel response and the time-frequency fingerprint of intruders. Numerical simulations show very low intrusion rates, and an experimental validation using a wireless test bed with programmable radios demonstrates the technique's effectiveness.