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Trust Management Scheme for Securing Vehicular Ad Hoc Networks Against Malicious Nodes and False Message Anomaly

Haewon ByeonConvergence Department Korea University of Technology and Education Cheonan Republic of KoreaMohammed E. SenoDepartment of Computer Sciences, College of Sciences University of Al Maarif Al Anbar IraqAjeet Kumar SrivastavaDepartment of Ece, School of Engineering and Technology Chhatrapati Shahu Ji Maharaj University Kanpur UP IndiaAzzah AlGhamdiComputer Information Systems Department, College of Computer Science and Information Technology Imam Abdalrhman Bin Faisal University Khobar Saudi ArabiaIsmail KeshtaComputer Science and Information Systems Department, College of Applied Sciences AlMaarefa University Riyadh Saudi ArabiaMukesh SoniDivision of Research and Development Lovely Professional University Phagwara IndiaKDV PrasadSymbiosis Institute of Business Management Hyderabad IndiaDilora AbdurakhimovaDepartment of Corporate Finance and Securities Tashkent State University of Economics Tashkent UzbekistanMohammed Wasim BhattModel Institute of Engineering and Technology Jammu J&K India
ABI

Аннотация

ABSTRACT With the rapid development of intelligent transportation systems presents significant opportunities for vehicular ad hoc networks (VANETs) present themselves; yet, these networks also encounter numerous security challenges. In order to maintain road safety and traffic efficiency, information is usually shared through communication between vehicle nodes or between vehicle nodes and roadside units (RSUs). Vehicle nodes, RSUs, and trusted authorities (TAs) constitute the majority of VANETs. An approach to hybrid trust management that is distributed, HTMS‐V, is presented to mitigate potential internal attackers and misleading messages in VANETs. This framework considers the attributes of VANETs and employs an enhanced subjective logic model to assess the trustworthiness of vehicle nodes through both direct and indirect trust metrics. Trust links among nodes are formed by information about interactions, and the trustworthiness of messages is determined by the degree of trust between nodes and the distance between them. The assessment outcomes are utilized to detect erroneous communications and malevolent nodes within the network. To assess the efficacy of the proposed approach, four distinct assault scenarios were devised for comparative experiments on the Veins vehicular network simulation platform. The experimental findings indicate that HTMS‐V proficiently withstands diverse attacks in VANETs, successfully detecting many false messages and malevolent nodes, even at a malicious node rate of 40%. The percentage of malicious nodes is 3%, 5%, 7%, and 9%, meaning that the overall rates of malicious nodes are 9%, 15%, 21%, and 27%. The malicious node anomaly detection accuracy of the HTMS‐V scheme was over 96%, the message judgment accuracy was over 95%, and the false positive rate was less than 4%.

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