A Data-Centric Approach to Taming the Message Dissemination in the Internet of Vehicles

Abstract

The Internet of Vehicles (IoV) aims to establish a network of autonomous and connected vehicles that communicate with one another and with road-side units (RSUs) and a central trust authority (TA). Messages must be efficiently and securely disseminated to conserve resources and preserve network security. Currently, there is much research on the security schemes and methods of disseminating messages. Furthermore, there is a deficiency of information regarding resource optimization. This paper takes an interdisciplinary approach by merging both cybersecurity and data science to optimize and secure the network. The proposed method applies Prim's algorithm to an existing vehicular security scheme, Privacy-Preserving Dual Authentication Scheme (PPDAS), to further network efficiency in terms of time consumption. When a dual authentication security scheme is in place, the time taken for message dissemination follows a quadratic growth; applying Prim's algorithm to the security scheme reduces the time to disseminate messages to a linear growth. The number of messages sent was decreased by a magnitude of up to 44.57. Contemporary security schemes are compared with PPDAS to justify the overhead consumption. The usage of network resources, such as time, is reduced, which substantially enhances the performance of the vehicular network and allows for the scalability of the IoV.