Key-Based Data Deduplication via Homomorphic NTRU for Internet of Vehicles

Abstract

In recent years, the gradual improvement of the Internet of Vehicles (IoV) ecosystem has highlighted the commercial potential of IoV. The IoV not only shows excellent performance in terms of road safety and driving comfort but also has great significance in terms of building new models of automobiles and transportation services. In addition, as the foundation of intelligent transportation, IoV has emerged as a research hotspot. However, the IoV has some shortcomings in terms of security, privacy, and storage of massive amounts of data. First, from the viewpoint of security and privacy, the transmission of encrypted data is bound to cause traffic wastage. Second, the massive amount of data stored in the cloud inevitably leads to data redundancy. To address the conflict between semantic security and data redundancy, this study formalizes a secure scheme for duplicated data that can prevent unnecessary storage and traffic on the cloud. This method ensures that an authorized intelligent connected vehicle (ICV) can logically outsource and retrieve data regardless of duplication. Under the premise of semantic security, a two-party deduplication protocol is constructed in terms of the homomorphic number theory research unit (NTRU). Our experimental results show that the proposed scheme is not only secure, but also able to provide complete semantic privacy without any third party. In the context of large-scale real-time IoV, this study not only provides a safe and reliable solution for data deduplication but also optimizes the efficiency of the solution.