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Growing computation requirements in emerging intelligently connected vehicle (ICV) networks has posed a big challenge for vehicles to process computation-intensive tasks on-board, and thus computation partition and offloading plays a critical role. Owing to broadcast nature of wireless channels, confidential messages without proper security protection in ICVs may be easily exposed to malicious users. In this paper, a mobile crowdsourcing (MCS) based mobile crowd computing framework for ICV networks is proposed, where multiple vehicles act as workers to provide computing services for end user (EU). In particular, artificial noise (AN) assisted physical (PHY) layer security approaches are used to enhance the security in offloading links. Ergodic secrecy rates in different offloading phases in time-varying channels are derived. In addition, an incentive-driven mechanism is introduced to encourage workers to share their idle computing resources, and an optimization problem is formulated to minimize the overall price paid for computing tasks, subject to energy consumption and delay constraints. Finally, Monte Carlo simulations verify the analysis on the ergodic secrecy rates. [ABSTRACT FROM AUTHOR]

Vehicle-to-vehicle (V2V) underlay cellular communication plays an important role in the fifth-generation (5G) and beyond communications and its security issues attract a lot of attention. Physical layer security, which explores channel characteristics to protect wireless communications, is very attractive due to its low latency. This paper focuses on secrecy capacity maximization in V2V underlay cellular communications, where the secrecy capacity of vehicular user equipments (VUEs) is optimized first, followed by sum proportional fairness function optimization for both VUEs and cellular user equipments (CUEs). The optimization problems can be solved in two sub-problems, e.g., power and subcarrier allocation problems. The power allocation can be done with the first strategy using a one-dimensional searching algorithm, whereas a genetic algorithm (GA) is used to solve the second optimization problem. In addition, as VUEs share uplink resources with CUEs, the co-channel interference exists and the subcarrier allocation sub-problem is a 3D search problem, which is solved by a two-step iterative Hungarian algorithm (IHA). Finally, simulations are performed to validate the performance of the proposed schemes. [ABSTRACT FROM AUTHOR]

This article aims to provide a comprehensive overview on PHY layer security assisted ICV networks. Beginning with a discussion from a general perspective of the ICV network architecture, this work summarizes the major security threats faced by ICV networks. To achieve confidential data transmission with a low latency and a high data rate, several physical layer security schemes are surveyed in this article, which include RRM, cooperative jamming, multi-antenna technologies, and PHY-layer key generation. In addition, the performances of the aforementioned schemes are compared in terms of different aspects, followed by a discussion on some major challenges that need to be tackled in the implementation of ICV networks. [ABSTRACT FROM AUTHOR]