PSI-CA-Based Vehicle Selection Scheme for Data Sharing in Internet of Vehicles

Abstract

In recent years, the development of the Internet of Vehicles (IoV) has led to an increase in the demand for data sharing services for the IoV. In the era of big data, safe and convenient data sharing services for IoV are inseparable from the support of reliable data. With the increase in the number of smart cars, how to filter the data provided by vehicles while protecting privacy to improve the quality of data sharing services has attracted the attention of scholars. However, in the existing data sharing scheme for IoV, the vehicles that provide data are selected based on the reputation mechanism or the voting mechanism. Our analysis shows that these two mechanisms lack objectivity and are vulnerable to cooperative attack. Therefore, based on spatiotemporal matching, a new trusted relationship establishment method, this paper proposes an objective and cooperative attack-resistant vehicle selection scheme for data sharing in IoV. Bloom filters and an exponential ElGamal encryption scheme are used to implement private set intersection cardinality (PSI-CA) technology for evaluating spatiotemporal matching level. In this paper, the scheme proposed is of great significance to improve existing vehicle services and improve driving safety.