Optimized Convolutional Neural Network Based Privacy Based Collaborative Intrusion Detection System for Vehicular Ad Hoc Network

International Journal of Electrical and Electronics Engineering

© 2023 by SSRG - IJEEE Journal

Volume 10 Issue 2

Year of Publication : 2023

Authors : M. Azath, Vaishali Singh

10.14445/23488379/IJEEE-V10I2P114

How to Cite?

M. Azath, Vaishali Singh, "Optimized Convolutional Neural Network Based Privacy Based Collaborative Intrusion Detection System for Vehicular Ad Hoc Network," SSRG International Journal of Electrical and Electronics Engineering, vol. 10,  no. 2, pp. 143-156, 2023. Crossref, https://doi.org/10.14445/23488379/IJEEE-V10I2P114

Abstract:

The Vehicular Adhoc Network (VANET) secures the communication of vehicles during information generation and transfer. Even though the lack of trust and privacy in this network questions the reliability of information exchange, to overcome this problem, we are designing a blockchain-based VANET framework to establish secure information exchange via blockchain technology and offer improved scalability, confidentiality, and privacy. This study uses an Improved K-Harmonics Mean Clustering (IKHMC) model for cluster formation in VANET. After that, a novel Hybrid Capuchin-based Rat Swarm Optimization (HCRSO) algorithm is used to select the cluster heads, which primarily aims to provide efficient energy utilization, throughput and delay minimization. We use the blockchain as a reliable and highly secure technology, and trust-based collaborative intrusion detection in the VANET model is performed using an optimized (Seagull Optimization) Convolutional Neural Network (CNN). Finally, the three intrusion classes, namely Distributed Daniel of Service (DDoS), Blackmailing and Sybil attacks with non-intrusion class, are classified. The blockchain-based collaborative intrusion detection model solves security issues and motivates (rewarding) vehicles to collaborate, and avoids repetitive detection processes. The experimental results show that the proposed methodology is efficient to be applied in resource-constrained vehicles and also shows bigger improvements in terms of malicious node detection, overhead, end-to-end delay, and energy utilization.

Keywords:

Blockchain, Security, Convolutional Neural Network, Ad-hoc, Vector routing protocol.

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