<p>Vehicular Ad-Hoc Networks (VANETs) enable communication between vehicles and infrastructure, supporting various applications that require secure access to sensitive data. Existing authentication approaches in VANETs commonly rely on analyzing driver behavior using vehicle sensor data. However, these approaches suffer from several limitations, including high computational cost, storage constraints, and reduced performance when processing raw driving data. Furthermore, existing solutions do not support secure and interoperable mechanisms for sharing authentication data among different vehicle manufacturers. This limitation remains a critical challenge that needs to be addressed to ensure real-world applicability. This study proposes a blockchain-based authentication framework that enables secure and interoperable driver authentication across heterogeneous vehicle manufacturers. To address storage and performance challenges, Correlation-based Feature Selection (CFS) is applied to reduce the size of raw driving data before storing it on the blockchain. This approach significantly decreases storage requirements while improving system efficiency. Experimental results demonstrate that the proposed framework improves authentication performance, achieving up to 99% accuracy using the KNN algorithm, while also increasing blockchain throughput in terms of Transactions Per Second (TPS). The proposed framework provides a scalable, secure, and efficient solution for cross-manufacturer authentication in VANET environments.</p>