Simulation is widely accepted in Vehicular Ad hoc Network (VANET) research due to the cost, safety and security issues associated with real world implementations and experimentation. However, several important factors must be considered if we expect the simulation results to be realistic, comparable and extendable to the real world, especially when it comes to security issues. These factors can largely be classed under three broad categories i.e. the Grid Pattern, the Communication Settings and the Mobility Pattern. Building on prior work, in this paper, we extend the simulation results of a VANET-based DDoS attack and an anomaly detection mechanism designed to detect the attack. We show that taken these factors into consideration leads to different results, affirming the need for considering these factors in simulations. We also discuss future research directions that result directly from our observations.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Exploring Realistic VANET Simulations for Anomaly Detection of DDoS Attacks


    Contributors:


    Publication date :

    2022-06-01


    Size :

    1504532 byte





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    Exploring Anomaly Detection Techniques for Enhancing VANET Availability

    Weber, Julia Silva / Ferreto, Tiago / Zincir-Heywood, Nur | IEEE | 2023


    Review of potential security attacks in VANET

    Shahid, Muhammad Anwar / Jaekel, Arunita / Ezeife, Christie et al. | IEEE | 2018


    Emulating a Realistic VANET Channel in Ns‐3

    Hilt, Benoit ;Berbineau, Marion ;Vinel, Alexey | Wiley | 2017


    WGL-VANET: A web-based visualization tool for VANET simulations

    Gocmenoglu, Can / Acarman, Tankut / Levrat, Bernard | IEEE | 2015


    Blockchain and Deep Learning-Based Decentralized Anomaly Detection Framework for VANET

    Jetani, Harshil / Patel, Janam / Mahida, Nikunjkumar et al. | IEEE | 2024