Malicious Data Traceability and Throughput Optimization Using Blockchain (IOTA Smart Contracts) for Next Generation Internet of Vehicles

Abstract

The Internet of Vehicles (IoV) faces security threats from malicious entities that endanger vehicles. However, traditional centralized networks have limitations in scalability, latency, and security. Decentralized blockchain architectures provide an alternative, though conventional blockchains also have restrictions. We develop an architecture based on IOTA's Directed Acyclic Graph (DAG) ledger tailored to IoV needs to enhance traceability, throughput, and security. The goal is to leverage IOTA's decentralized, high throughput, low latency design to overcome limitations in existing IoV networks. We propose an IOTA-based model using smart contracts for malicious data/user tracing and timing side-channels for attack detection. We adaptively schedule data to optimize throughput based on traffic conditions. Our simulations compare throughput, latency, and attack detection across varied scenarios. Our results demonstrate that the architecture enables automated security via decentralized consensus, avoiding centralized failures. The smart contracts facilitate real-time threat tracing and mitigation. Timing analysis reveals IOTA's ability to identify attacks through latency fluctuations. Optimized data transfer scheduling adapts to congestion levels. Overall, integrating reputation systems, smart contracts, and IOTA's innovations significantly improves security, efficiency, and scalability compared to centralized and blockchain IoV networks. This work advances IoV security by outlining a comprehensive blockchain solution leveraging IOTA's unique capabilities. The decentralized mechanisms enhance traceability and trust while optimizing performance tailored to vehicular demands. This establishes a foundation for reliable and safe autonomous driving through innovations in distributed ledger technology.