Proposed Hybrid Secured Method to Protect Against DDOS in n Vehicular Adhoc Network (VANET)

Security and safety are critical concerns in Vehicular Adhoc Networks. vulnerable to Distributed Denial of Service (DDoS) attacks, which occur when multiple vehicles carry out various tasks. This cause disrupts the normal functioning legitimate routes. In this work, Hybrid PSO-BAT Optimization Algorithm (HBPSO) based on modified chaos -cellular neural network (Chaos - CNN) approaches has been proposed overcome DDoS attacks. The suggest consists three-part hybrid optimization search algorithm enhance route from source destination, theory module is used detect abnormal nodes, then Modified Chaotic CNN (MCCN) employed prevent a malicious node sending data destination by determining that consumer more resource, packets lose or victim could reset path between attacker itself. CICIDS dataset test evaluate performance approach criteria accuracy, packet loss, jitter. Chaos approached results outperform similar models related work protects VANETs with high accuracy 0.8736, specificity 0.9959, TPR 0.9561, FPR 0.78, Detection rate 0.9561.