Blockchain-Based Enhanced Secure Data Storage Model: A Framework for the Internet of Vehicle Networks

The Internet of Vehicles (IoV) has gained significant attention due to its capability to facilitate Vehicle-to-Vehicle (V2V) and Vehicle-to-Infrastructure (V2I) communication. However, IoV networks are highly susceptible to security and privacy threats, including unauthorized tracking of vehicle locations and Distributed Denial-of-Service (DDoS) attacks. To address these challenges, recent studies have explored blockchain technology as a potential solution for enhancing data security and privacy in IoV networks. This research proposes a blockchain-based enhanced secure data storage model for IoV networks, incorporating lightweight cryptography algorithms to ensure robust security. Additionally, the framework integrates statistical and machine learning models to analyze harvested vehicular data, providing predictive insights for threat detection and mitigation. The study presents a hypothetical V2V communication dataset comprising eleven attributes and four records representing a four-smart-vehicle scenario. Analysis of vehicular speed data reveals an average speed of 55 km/h, with maximum and minimum speeds of 100 km/h and 0 km/h, respectively. The total payload transmitted is 42 KB, with an average payload size of 10.5 KB. A key contribution of this study is the development of a Solana blockchain-based secure data storage model, where transactions are automated and validated through smart contracts. The model efficiently stores the large volume of data generated by smart vehicles and enables real-time data retrieval using embedded internet protocols. The proposed framework is expected to provide a highly secure IoV data storage system upon successful implementation while enhancing threat prediction accuracy and overall network security.