Social networking and big data analytics assisted reliable recommendation system model for internet of vehicles

Abstract

The devices are becoming ubiquitous and interconnected due to rapid advancements in computing and communication technology. The Internet of Vehicles (IoV) is one such example which consists of vehicles that converse with each other as well as with the public networks through V2V (vehicle-to-vehicle), V2P (vehicle-to-pedestrian) and V2I (vehicle-to-infrastructure) communications. The social relationships amongst vehicles create a social network where the participants are intelligent objects rather than the human beings and this leads to emergence of Social Internet of Vehicles (SIoV). The big data generated from these networks of devices are needed to be processed intelligently for making these systems smart. The security and privacy issues such as authentication and recognition attacks, accessibility attacks, privacy attacks, routing attacks, data genuineness attacks etc. are to be addressed to make these cyber physical network systems very reliable. This paper presents a comprehensive survey on SIoV and proposes a novel social recommendation model that could establish links between social networking and SIoV for reliable exchange of information and intelligently analyze the information to draw authentic conclusions for making right assessment. The future Intelligent IoV system which should be capable to learn and explore the cyber physical system could be designed.