Blockchain Integration with AI for Secure Data Sharing in Connected Vehicles

Abstract

Linked automobile networks benefit from real-time V2X communication for safety, traffic management, and user experience. These benefits show reliable connected car data security, privacy, and integrity. A public, decentralised, unchangeable blockchain may overcome these issues. Automotive AI's complex learning and adaptive algorithms have changed data processing and decision-making. Connected automobile data is protected by blockchain and AI. 

Data sharing between cars is safe with trust. Blockchain's DLT establish trust. To prevent manipulation, blockchain transactions and data are encrypted and time-stamped. Central database mistakes are avoided via blockchain. Data breaches and cyberattacks are prevented. Research believes blockchain may improve vehicle network connectivity, authentication, and data verification. 

Blockchain architecture is improved by AI analysing enormous volumes of real-time data and extracting relevant information using machine learning and deep learning. AI systems may use big data to predict, discover patterns, and adjust data-sharing protocols. Blockchain data flow inconsistencies may indicate compromise using AI. A real-time security detection and response is possible. Making V2V and V2I data transfers safer and quicker, AI may automate complex decision-making. 

Restore automobile data using AI-blockchain. Transactions hinder blockchain speed, hence many question its scalability. Sharding and smart contracts secure big data. To improve operations, AI anticipates data flow and prioritises high-priority transfers. Balanced blockchain nodes reduce congestion. 

Data encryption research using blockchain and AI. Fundamental data security is examined using PKI, ZKPs, and homomorphic encryption. Threat-adaptive encryption and key management by AI algorithms make data sharing and access tougher for hackers.
Blockchain and AI solve regulatory and compliance challenges for autonomous and semi-autonomous cars sharing data. Transparent, irreversible blockchain protects data and GDPR. Analysis of AI auditing and reporting. Automation might boost regulatory compliance. 

Blockchain and AI endanger auto security. Resources may be scarce, blockchain protocols may fail, and automakers may use other AI models. Based on research and development, this article presents hybrid blockchain models, federated AI training across decentralised networks, and modular protocol frameworks for system integration. 

Blockchain and AI are used by IT and auto-linked automobile pioneers. Case studies demonstrate innovation, challenges, and success. Blockchain and AI networks may improve vehicle-infrastructure connectivity, safety, and data sharing.

Transport will alter with AI and blockchain. Technology may increase self-driving, data networking, and automotive safety. Consider quantum-resistant encryption for quantum computing data security. AI must be growth-friendly for blockchain. Regulatory changes with networked cars. Legislation must be flexible to protect user privacy and data while permitting innovation.