Secure Vehicular Communications With Varying QoS and Environments: A Unified Cross-Layer Policy-Adaptation Approach

With the ubiquitous connectivity in internet of vehicles, secure transmission is of vital importance for intelligent vehicle-to-everything (V2X) communications. However, in order to effectively guarantee the secrecy performance, once the short-term statistics of channel quality are low, which frequently happens because of the high mobility of vehicles, the throughput performance can be weakened by using the existing either cryptography techniques or physical-layer security (PLS) technique. To improve the throughput of secure data transmission, we propose the concept of statistical security, which utilizes the time-sensitive characteristics of information, such as the position of mobile vehicles, in V2X communications. Specifically, the time-sensitive information has its own outdated rate. As long as the information leakage rate is less than the information outdated rate, the eavesdropper still cannot obtain any useful information. Then, we use a queue system to characterize the eavesdropping process, where the queue-length violation probability indicates the level of secure transmission. Under this statistical security model, we investigate the throughput maximization problem and give the optimal power allocation scheme for the legitimate vehicular users. Furthermore, since the service’s security QoS requirements and wireless environments are both varying in V2X communications, we propose a unified cross-layer policy-adaption approach to guarantee the varying security QoS requirements meanwhile improving the throughput. Simulation results verify that our proposed approach significantly outperforms the existing baseline schemes.