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This is a Experimental Study study.

Design and Optimization of a Blockchain‐Enabled Decentralized Security Framework for Anomaly Detection in VANETs

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This study demonstrates a decentralized security framework for anomaly detection in VANETs, highlighting efficiency and accuracy improvements.

The proposed framework achieves 94.2% precision in detecting sophisticated attacks in VANETs.
Improvements in consensus efficiency reduced verification latency by over 40% through enhanced protocols.
A multi-layer blockchain architecture supports transparent and secure interactions among vehicle nodes.
Integration of machine learning algorithms allows for effective analysis of traffic patterns to identify intrusions.

Tan et al. (2025) studied this question.

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This study demonstrates a decentralized security framework for anomaly detection in VANETs, highlighting efficiency and accuracy improvements.