Collaborative detection of black hole and gray hole attacks for secure data communication in VANETs
Vehicle ad hoc networks (VANETs) are vital towards the success and comfort of self-driving as well as semi-automobile vehicles. Such vehicles rely heavily on data management and the exchange of Cooperative Awareness Messages (CAMs) for external communication with the environment. VANETs are vulnerab...
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Multidisciplinary Digital Publishing Institute
2022
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Online Access: | https://eprints.ums.edu.my/id/eprint/36423/1/ABSTRACT.pdf https://eprints.ums.edu.my/id/eprint/36423/2/FULLTEXT.pdf https://eprints.ums.edu.my/id/eprint/36423/ https://doi.org/10.3390/app122312448 |
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my.ums.eprints.364232023-08-17T04:00:32Z https://eprints.ums.edu.my/id/eprint/36423/ Collaborative detection of black hole and gray hole attacks for secure data communication in VANETs Shamim Younas Faisal Rehman Tahir Maqsood Saad Mustafa Adnan Akhunzada Abdullah Gani TE210-228.3 Construction details Including foundations, maintenance, equipment Vehicle ad hoc networks (VANETs) are vital towards the success and comfort of self-driving as well as semi-automobile vehicles. Such vehicles rely heavily on data management and the exchange of Cooperative Awareness Messages (CAMs) for external communication with the environment. VANETs are vulnerable to a variety of attacks, including Black Hole, Gray Hole, wormhole, and rush attacks. These attacks are aimed at disrupting traffic between cars and on the roadside. The discovery of Black Hole attack has become an increasingly critical problem due to widespread adoption of autonomous and connected vehicles (ACVs). Due to the critical nature of ACVs, delay or failure of even a single packet can have disastrous effects, leading to accidents. In this work, we present a neural network-based technique for detection and prevention of rushed Black and Gray Hole attacks in vehicular networks. The work also studies novel systematic reactions protecting the vehicle against dangerous behavior. Experimental results show a superior detection rate of the proposed system in comparison with state-of-the-art techniques. Multidisciplinary Digital Publishing Institute 2022-12-05 Article NonPeerReviewed text en https://eprints.ums.edu.my/id/eprint/36423/1/ABSTRACT.pdf text en https://eprints.ums.edu.my/id/eprint/36423/2/FULLTEXT.pdf Shamim Younas and Faisal Rehman and Tahir Maqsood and Saad Mustafa and Adnan Akhunzada and Abdullah Gani (2022) Collaborative detection of black hole and gray hole attacks for secure data communication in VANETs. Applied Sciences, 12. pp. 1-17. https://doi.org/10.3390/app122312448 |
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TE210-228.3 Construction details Including foundations, maintenance, equipment Shamim Younas Faisal Rehman Tahir Maqsood Saad Mustafa Adnan Akhunzada Abdullah Gani Collaborative detection of black hole and gray hole attacks for secure data communication in VANETs |
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Vehicle ad hoc networks (VANETs) are vital towards the success and comfort of self-driving as well as semi-automobile vehicles. Such vehicles rely heavily on data management and the exchange of Cooperative Awareness Messages (CAMs) for external communication with the environment. VANETs are vulnerable to a variety of attacks, including Black Hole, Gray Hole, wormhole, and rush attacks. These attacks are aimed at disrupting traffic between cars and on the roadside. The discovery of Black Hole attack has become an increasingly critical problem due to widespread adoption of autonomous and connected vehicles (ACVs). Due to the critical nature of ACVs, delay or failure of even a single packet can have disastrous effects, leading to accidents. In this work, we present a neural network-based technique for detection and prevention of rushed Black and Gray Hole attacks in vehicular networks. The work also studies novel systematic reactions protecting the vehicle against dangerous behavior. Experimental results show a superior detection rate of the proposed system in comparison with state-of-the-art techniques. |
format |
Article |
author |
Shamim Younas Faisal Rehman Tahir Maqsood Saad Mustafa Adnan Akhunzada Abdullah Gani |
author_facet |
Shamim Younas Faisal Rehman Tahir Maqsood Saad Mustafa Adnan Akhunzada Abdullah Gani |
author_sort |
Shamim Younas |
title |
Collaborative detection of black hole and gray hole attacks for secure data communication in VANETs |
title_short |
Collaborative detection of black hole and gray hole attacks for secure data communication in VANETs |
title_full |
Collaborative detection of black hole and gray hole attacks for secure data communication in VANETs |
title_fullStr |
Collaborative detection of black hole and gray hole attacks for secure data communication in VANETs |
title_full_unstemmed |
Collaborative detection of black hole and gray hole attacks for secure data communication in VANETs |
title_sort |
collaborative detection of black hole and gray hole attacks for secure data communication in vanets |
publisher |
Multidisciplinary Digital Publishing Institute |
publishDate |
2022 |
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https://eprints.ums.edu.my/id/eprint/36423/1/ABSTRACT.pdf https://eprints.ums.edu.my/id/eprint/36423/2/FULLTEXT.pdf https://eprints.ums.edu.my/id/eprint/36423/ https://doi.org/10.3390/app122312448 |
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1775623862635986944 |
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13.18916 |