Bilateral Content Recommendation for Intelligent Connected Vehicles: Challenges and Applications

Content recommendation, as a fundamental functionality of intelligent connected vehicles, drives many real applications, such as advertisement recommendations and car-hailing services. Currently, the bilateral content recommendation has emerged as a promising content recommendation paradigm where both parties can specify policies for the other, significantly improving users’ personal experience. In this article, we study the practical requirements for bilateral content recommendation in intelligent connected vehicles in terms of data security and functionality. Subsequently, we summarize current state-of-the-art bilateral content recommendation schemes and discuss how to implement these schemes in real advertisement recommendations and car-hailing services. With the assistance of these bilateral content recommendations, both parties are allowed to specify policies and the content can be decrypted if and only if both parties’ policies are satisfied simultaneously. This not only protects data security but also helps users filter useless content. Finally, we summarize several promising research directions in bilateral content recommendations for intelligent connected vehicles and discuss the potential solutions and corresponding challenges.