Open Access

ARTICLE

Secure and Reliable Routing in the Internet of Vehicles Network: AODV-RL with BHA Attack Defense

Nadeem Ahmed^1,*, Khalid Mohammadani², Ali Kashif Bashir^3,4,5, Marwan Omar⁶, Angel Jones⁷, Fayaz Hassan¹

1 School of Electronic Science, Beijing University of Post and Telecommunication, Beijing, 100086, China
2 Department of Computer Science, Huanggang Normal University, Huanggang, China
3 Department of Computing and Mathematics, Manchester Metropolitan University, Manchester, UK
4 Woxsen School of Business, Woxsen University, Hyderabad, 502345, India
5 Department of Computer Science and Mathematics, Lebanese American University, Beirut, Lebanon
6 Information Technology and Management, Illinois Institute of Technology, Chicago, USA
7 College of Computing, Capital Technology University, Laurel, USA

* Corresponding Author: Nadeem Ahmed. Email:

(This article belongs to the Special Issue: Cooperative ML/DL and Intelligent Networks towards Vehicle Health Monitoring System (VHMS))

Computer Modeling in Engineering & Sciences 2024, 139(1), 633-659. https://doi.org/10.32604/cmes.2023.031342

Received 05 June 2023; Accepted 18 September 2023; Issue published 30 December 2023

Abstract

Wireless technology is transforming the future of transportation through the development of the Internet of Vehicles (IoV). However, intricate security challenges are intertwined with technological progress: Vehicular ad hoc Networks (VANETs), a core component of IoV, face security issues, particularly the Black Hole Attack (BHA). This malicious attack disrupts the seamless flow of data and threatens the network’s overall reliability; also, BHA strategically disrupts communication pathways by dropping data packets from legitimate nodes altogether. Recognizing the importance of this challenge, we have introduced a new solution called ad hoc On-Demand Distance Vector-Reputation-based mechanism Local Outlier Factor (AODV-RL). The significance of AODV-RL lies in its unique approach: it verifies and confirms the trustworthiness of network components, providing robust protection against BHA. An additional safety layer is established by implementing the Local Outlier Factor (LOF), which detects and addresses abnormal network behaviors. Rigorous testing of our solution has revealed its remarkable ability to enhance communication in VANETs. Specifically, Our experimental results achieve message delivery ratios of up to 94.25% and minimal packet loss ratios of just 0.297%. Based on our experimental results, the proposed mechanism significantly improves VANET communication reliability and security. These results promise a more secure and dependable future for IoV, capable of transforming transportation safety and efficiency.

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Keywords

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