Vehicular Ad-hoc networks (VANETs) which is regarded to be a major component in the intelligent transportation systems, have the defined target of assuring safe delivery of information between the vehicles.These networks consist of several essential elements, such as dynamic changing nodes, scattered networks, sensors, road-side components (RSC) and self-organizing topologies.But these networks are more vulnerable to the contentious attacks, security breaches and data privacy problems persist as a crucial threat in spite of the recent advancement of VANET.To overcome this challenge, an effective and high secured framework is mandatorily demanded.Consequently, this research introduces a novel routing framework that integrates the attack detection and hybrid encryption units.The cluster head (CH) is determined utilising novel gated sway networks, which combine centrality-based feature extraction with a gated neural network to ensure trusted CH selection.This enhances resilience and improves interfacing throughout the data transmission process in the VANET framework.The hybrid encryption schemes contain sandwich Henon maps (SHM) coupled with the Advanced Encryption schemes (AES).This combination strives to strengthen the network's security and privacy The proposed protocols are analysed using SUMO-OMNET++ simulation environment.Nearly 2,50,000 data traces comprise of normal and attack data were simulated and attacks such as sybil and wormhole attacks are injected using python 3.19 programming.Simulation results from the performance assessment demonstrate that the proposed framework has produced the 96.5% detection accuracy, 96.0% precision, 95.7% recall, 96.4% specificity, 97.5% F1-Score and it is apparent that the proposed framework has exhibited the better performance over other existing algorithms.Additionally, National Institute of Standard Technique (NIST) suite was performed to verify the randomness of the encrypted bits utilising the recommended method.The test outcomes demonstrated that the suggested encryption approach has produced the high randomness features capable of protecting the sybil and gray hole attacks.
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Anjali et al. (2025) studied this question.
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