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      A Review on Data Falsification-Based attacks In Vehicular Ad Hoc Network

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            Abstract

            Cooperative Intelligent Transportation System (cITS) is one of IoT applications whose purpose is to enhance drive safety and efficiency. Several components constitute cITS including vehicles, roadside units, and backend systems. Like many IoT applications and systems, cITSs are susceptible to a wide-range of intruding or misbehaving attacks that could be launched by attackers from inside or outside of the network. Once a vehicle is compromised, it can be used to launch several types of attacks against other vehicles and/or components of cITS. They can also be used to send false information and messages to the neighboring vehicles, causing severe complications such as traffic congestions and accidents. Such attacks impede the momentum of the integration of cITS technology with existing infrastructure. In this paper, a comprehensive and deep analysis of the state-of-the-art solutions in intrusion and misbehavior detection for cITS have been conducted. This paper mainly focuses on the data falsification-based attacks that manipulate the mobility data and messages shared with the neighboring vehicles as it is more challenging and difficult to identify and mitigate. The paper can be of great use for research community to explore more opportunities and new avenues and propose more robust and effective security solutions that protect the potential applications in cITSs

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            Author and article information

            Journal
            ScienceOpen Posters
            ScienceOpen
            14 February 2022
            Affiliations
            [1 ] Computer Science Department, University of Idaho, Moscow, ID, USA
            Author notes
            Author information
            https://orcid.org/0000-0003-4534-2461
            Article
            10.14293/S2199-1006.1.SOR-.PPK2IAS.v1
            3a8f8daa-0656-41ba-861a-b04cfb0f2ba4

            This work has been published open access under Creative Commons Attribution License CC BY 4.0 , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Conditions, terms of use and publishing policy can be found at www.scienceopen.com .

            History
            : 14 February 2022

            The datasets generated during and/or analysed during the current study are available in the repository: https://data.transportation.gov/Automobiles/Next-Generation-Simulation-NGSIM-Vehicle-Trajector/8ect-6jqj
            Computer science,Mathematics
            Internet of Things,Misbehavior Detection Systems,Intrusion Detection Systems,Smart Car,Cooperative Intelligent Transportation Systems

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