mca 18: e2

Research Article

Performance Analysis of RACODSR Protocol in Smart Grayhole Attacks on VANets

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  • @ARTICLE{10.4108/eai.1-6-2022.174088,
        author={Kaoutar Ourouss and Najib Naja and Abdellah Jamali},
        title={Performance Analysis of RACODSR Protocol in Smart Grayhole Attacks on VANets},
        journal={EAI Endorsed Transactions on Mobile Communications and Applications: Online First},
        volume={},
        number={},
        publisher={EAI},
        journal_a={MCA},
        year={2022},
        month={6},
        keywords={Mobile ad hoc networks, Vehicular networks, DDoS Attacks, Reputation System, Trust Management, ACO},
        doi={10.4108/eai.1-6-2022.174088}
    }
    
  • Kaoutar Ourouss
    Najib Naja
    Abdellah Jamali
    Year: 2022
    Performance Analysis of RACODSR Protocol in Smart Grayhole Attacks on VANets
    MCA
    EAI
    DOI: 10.4108/eai.1-6-2022.174088
Kaoutar Ourouss1,*, Najib Naja1, Abdellah Jamali1
  • 1: National Institute of Posts and Telecommunications, Rabat, National School of Applied Sciences, Berrchid, Morocco
*Contact email: ourouss@inpt.ac.ma

Abstract

As a subclass of Mobile Adhoc Networks (MANets), Vehicular Ad Hoc Network (VANET) is a set of interconnecting vehicles that aim to provide a wide spectrum of encouraging road services, such as safety and traffic management. This key component of Intelligent Transportation Systems (ITS), is impacted by the vehicle’s mobility and suffers from frequent link disruptions caused voluntarily or intentionally by malicious attackers, which make the security issue more challenging and even life-threatening when critical attacks occurred. This work focuses on analyzing the smart grayhole attacks within VANets environments and evaluating the Reputation-based Ant Colony Optimization Dynamic Source Routing (RACODSR) and Dynamic Source Routing (DSR) protocols performances under two different scenarios. For this purpose, VANets mobility models with and without collisions are generated using OpenStreetMap and Simulation of Urban Mobility (SUMO) tools and simulated in Network Simulator NS2 to assess the effectiveness of the compared protocols using the Drop rate, Packet Delivery Ratio, Throughput, Jitter, End-to-End delay, and consumed energy metrics.