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Hybrid Security Against Black Hole and Sybil Attacks in Drone-Assisted Vehicular Ad Hoc Networks

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Intelligent Data Engineering and Analytics (FICTA 2023)

Part of the book series: Smart Innovation, Systems and Technologies ((SIST,volume 371))

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Abstract

Vehicular ad hoc networks (VANETs) are one among the trending research area, and it is utilized in maximum of the intelligent transmission system (ITS) based application. The major challenges which are present during the process of communication between the vehicles are delay due obstacles in ground level and packet loss due to attacks. As so to overcome this drawbacks, hybrid security-based drones-assisted VANETs are introduced in this paper. The proposed approach is based on three transmission models such as (i) vehicle to vehicle (V-V), vehicle to drone (V-D), and drone to drone (D-D). Drones are launched in the VANET network to create the obstacles-free communication. Hybrid security is performed in two stages, at the initial stage—trusted flag-based security is provided to both the V-V and V-D communication models. Secondly, trust evaluation is performed in D-D communication through trust score calculation. To analyze the performance of the hybrid security approach, black hole and Sybil attacks are introduced in the network. The parameters which are considered for the performance analysis are packet delivery ratio, throughput, packet loss, and delay. The values are calculated, and it is compared with the RSAH method in terms of black hole and Sybil attack. Finally, the proposed hybrid security approach achieves (9%) higher packet delivery ratio, (200 Kbps) higher throughput, (350 packets) lower packet loss, and (150 ms) lower delay when compared with the earlier method.

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Author information

Authors and Affiliations

  1. Department of Computer Technical Engineering, Bilad Alrafidain University College, Baghdad, Diyala, 32001, Iraq

    Aryan Abdlwhab Qader

  2. Department of Computer Technical Engineering, College of Information Technology, Imam Ja’afar Al-Sadiq University, Baghdad, Al-Muthanna, 66002, Iraq

    Mohammed Hasan Mutar

  3. University of Mashreq, Research Center, Baghdad, Iraq

    Sameer Alani

  4. Department of Medical Instruments Engineering Techniques, Al-Farahidi University, Baghdad, Iraq

    Waleed Khalid Al-Azzawi

  5. Computer Technology Engineering, College of Engineering Technology, Al-Kitab University, Altun Kupri, Iraq

    Sarmad Nozad Mahmood

  6. Department of Computer Techniques Engineering, Mazaya University College, Dhi-Qar, Annasiriyah, 64001, Iraq

    Hussein Muhi Hariz

  7. Department of Medical Device Industry Engineering, College of Engineering Technology, National University of Science and Technology, Dhi Qar, Iraq

    Mustafa Asaad Rasol

Authors
  1. Aryan Abdlwhab Qader
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  2. Mohammed Hasan Mutar
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  3. Sameer Alani
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  4. Waleed Khalid Al-Azzawi
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  5. Sarmad Nozad Mahmood
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  6. Hussein Muhi Hariz
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  7. Mustafa Asaad Rasol
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Corresponding author

Correspondence to Aryan Abdlwhab Qader .

Editor information

Editors and Affiliations

  1. Department of Electronics Engineering, Faculty of Engineering and Technology (UNSIET), Veer Bahadur Singh Purvanchal University, Jaunpur, Uttar Pradesh, India

    Vikrant Bhateja

  2. Cardiff School of Technologies, Cardiff Metropolitan University, Cardiff, Warwickshire, UK

    Fiona Carroll

  3. Faculty of Engineering, University of Porto, Porto, Portugal

    João Manuel R. S. Tavares

  4. Cardiff Metropolitan University, Cardiff, Warwickshire, UK

    Sandeep Singh Sengar

  5. Faculty of Computer and Information Science, University of Ljubljana, Ljubljana, Slovenia

    Peter Peer

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© 2023 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

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Qader, A.A. et al. (2023). Hybrid Security Against Black Hole and Sybil Attacks in Drone-Assisted Vehicular Ad Hoc Networks. In: Bhateja, V., Carroll, F., Tavares, J.M.R.S., Sengar, S.S., Peer, P. (eds) Intelligent Data Engineering and Analytics. FICTA 2023. Smart Innovation, Systems and Technologies, vol 371. Springer, Singapore. https://doi.org/10.1007/978-981-99-6706-3_34

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