Open Access

ARTICLE

Blockchain Driven Metaheuristic Route Planning in Secure Vehicular Adhoc Networks

Siwar Ben Haj Hassine¹, Saud S. Alotaibi², Hadeel Alsolai³, Reem Alshahrani⁴, Lilia Kechiche⁵, Mrim M. Alnfiai⁶, Amira Sayed A. Aziz⁷, Manar Ahmed Hamza^8,*

1 Department of Computer Science, College of Science & Art at Mahayil, King Khalid University, Saudi Arabia
2 Department of Information Systems, College of Computing and Information System, Umm Al-Qura University, Saudi Arabia
3 Department of Information Systems, College of Computer and Information Sciences, Princess Nourah Bint Abdulrahman University, P.O. Box 84428, Riyadh, 11671, Saudi Arabia
4 Department of Computer Science, College of Computers and Information Technology, Taif University, P.O.Box 11099, Taif, 21944, Saudi Arabia
5 Department of Sciences and Technology, Taif University, Taif P.O. Box 11099, Taif, 21944, Saudi Arabia
6 Department of Information Technology, College of Computers and Information Technology, Taif University, Taif P.O. Box 11099, Taif, 21944, Saudi Arabia
7 Department of Digital Media, Faculty of Computers and Information Technology, Future University in Egypt, New Cairo, 11835, Egypt
8 Department of Computer and Self Development, Preparatory Year Deanship, Prince Sattam bin Abdulaziz University, AlKharj, Saudi Arabia

* Corresponding Author: Manar Ahmed Hamza. Email:

Computers, Materials & Continua 2022, 73(3), 6461-6477. https://doi.org/10.32604/cmc.2022.032353

Received 15 May 2022; Accepted 17 June 2022; Issue published 28 July 2022

Abstract

Nowadays, vehicular ad hoc networks (VANET) turn out to be a core portion of intelligent transportation systems (ITSs), that mainly focus on achieving continual Internet connectivity amongst vehicles on the road. The VANET was utilized to enhance driving safety and build an ITS in modern cities. Driving safety is a main portion of VANET, the privacy and security of these messages should be protected. In this aspect, this article presents a blockchain with sunflower optimization enabled route planning scheme (BCSFO-RPS) for secure VANET. The presented BCSFO-RPS model focuses on the identification of routes in such a way that vehicular communication is secure. In addition, the BCSFO-RPS model employs SFO algorithm with a fitness function for effectual identification of routes. Besides, the proposed BCSFO-RPS model derives an intrusion detection system (IDS) encompassing two processes namely feature selection and classification. To detect intrusions, correlation based feature selection (CFS) and kernel extreme machine learning (KELM) classifier is applied. The performance of the BCSFO-RPS model is tested using a series of experiments and the results reported the enhancements of the BCSFO-RPS model over other approaches with maximum accuracy of 98.70%.

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Keywords

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