Interaction Trust-Driven Data Distribution for Vehicle Social Networks: A Matching Theory Approach

Due to the rapid expansion of the Internet of Vehicles (IoVs), service providers deploy roadside units (RSUs), and base stations (BSs) close to vehicles. They can provide vehicles with computational offloading services quickly. In the context of vehicle social networks, where vehicles can communicate and share data with each other, the security and efficiency of data distribution are crucial. Unfortunately, the open nature of RSU BSs makes them vulnerable to malicious attackers, hence affecting the quality of the user experience. This article proposes a security trust degree incentive-based evaluation mechanism that calculates the security trust degree of vehicle users to RSU BSs through the continuous interaction between them in order to effectively address the aforementioned issues. Additionally, taking into account the competitive nature of task computation offloading between vehicle users and BSs, a stable matching algorithm is used to match each vehicle user with the most appropriate BS so that they can work together to prevent competition in task offloading and improve task offloading efficiency. Due to the limited number of BS matches and the dynamic position changes of vehicle users, we further increase the data distribution efficiency by calculating the vehicle user degree of relationship and connection probability to match vehicle users with similar preferences. Finally, our proposed scheme is validated via numerous simulations with enhanced security service performance in terms of vehicle task offloading, while data distribution efficiency are effectively improved.