In this paper, we discussed the brief overview of SDN security survey, we specifically investigate the potential lt heats of man-in-the-middle attacks on the Open Flow control channel, we also describe a feasible attack model in the open flow channel, and then we implement attack demonstrations to show the severe consequences of such attacks. Additionally, we propose a lightweight countermeasure using Bloom filters. We implement a prototype for this method to monitor stealthy packet modifications. The successful attacks can effectively poison the Virtual Machine information, a fundamental building block for core SDN components and topology-aware SDN applications. With the poisoned network visibility, the upper-layer Open Flow controller services/apps may be totally misled, leading to serious hijacking, denial of service or man-in-the-middle attacks. The result of our evaluation shows that our Bloom filter monitoring system is efficient and consumes few resources


    Access

    Download


    Export, share and cite



    Title :

    PROVIDING SECURITY AGAINST IP CROWDSOURCED SPOOFING ATTACKS ON CLOUD USING TOPOGUARD ALGORITHM


    Contributors:
    M, KEERTHIVASAN (author) / R, KISHORE (author) / M, MALATHI (author) / G, MONICA (author) / V, SENTHILKUMAR (author) / K, KUMARESAN (author) / K, DINESHKUMAR (author)

    Publication date :

    2019-04-06


    Remarks:

    South Asian Journal of Engineering and Technology; Vol 8 No S 1 (2019): Volume 8, Supplementary Issue 1, Year 2019; 158-165 ; 2454-9614


    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English


    Classification :

    DDC:    629



    Firms urged to tighten security after spoofing attacks

    British Library Online Contents | 2003


    A Radar System With Adaptive Waveform Selection Against Dynamic Spoofing Attacks

    Xie, Chao / Liu, Guanghua / Xu, You et al. | IEEE | 2025


    On Jamming Attacks in Crowdsourced Air Traffic Surveillance

    Leonardi, Mauro / Strohmeier, Martin / Lenders, Vincent | IEEE | 2021


    Detecting ADS-B Spoofing Attacks using Deep Neural Networks

    Ying, Xuhang / Mazer, Joanna / Bernieri, Giuseppe et al. | ArXiv | 2019

    Free access