Recent research in secure routing for Vehicular Ad Hoc Networks focuses on designing intelligent and resilient communication mechanisms that safeguard data transmission against diverse cyber threats such as black-hole, wormhole, and Sybil attacks. Researchers are leveraging artificial intelligence, blockchain, and trust-based models to enhance the reliability and confidentiality of routing decisions in highly dynamic vehicular environments. Machine learning and deep learning algorithms are being applied to predict malicious behaviors, optimize route selection, and ensure adaptive protection under real-time conditions. Blockchain-integrated frameworks provide decentralized authentication and immutability of routing information, while lightweight cryptographic schemes are introduced to balance security with energy efficiency. Overall, these advancements aim to establish robust, privacy-preserving, and scalable secure routing protocols that ensure safe and efficient data communication in next-generation vehicular networks.