• DocumentCode
    166976
  • Title

    Assessing the impact of intra-cloud live migration on anomaly detection

  • Author

    Shirazi, Noor-ul-Hassan ; Simpson, Steven ; Marnerides, Angelos K. ; Watson, Michael ; Mauthe, Andreas ; Hutchison, David

  • Author_Institution
    InfoLab21, Lancaster Univ., Lancaster, UK
  • fYear
    2014
  • fDate
    8-10 Oct. 2014
  • Firstpage
    52
  • Lastpage
    57
  • Abstract
    Virtualized cloud environments have emerged as a necessity within modern unified ICT infrastructures and have established themselves as a reliable backbone for numerous always-on services. `Live´ intra-cloud virtual-machine (VM) migration is a widely used technique for efficient resource management employed within modern cloud infrastructures. Despite the benefits of such functionality, there are still several security issues which have not yet been thoroughly assessed and quantified. We investigate the impact of live virtual-machine migration on state-of-the-art anomaly detection (AD) techniques (namely PCA and K-means), by evaluating live migration under various attack types and intensities. We find that the performance for both detectors degrades as shown by their Receiver Operating Characteristics (ROC) curves when intra-cloud live migration is initiated while VMs are under a netscan (NS) or a denial-of-service (DoS) attack.
  • Keywords
    cloud computing; computer network security; virtual machines; K-means; PCA; ROC curves; anomaly detection; denial-of-service attack; intracloud live migration; live intracloud virtual-machine migration; netscan; receiver operating characteristic curves; resource management; security issues; virtualized cloud environments; Computer crime; Conferences; Detectors; Entropy; Feature extraction; Principal component analysis; Vectors; Cloud computing; anomaly detection; live VM migration;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Cloud Networking (CloudNet), 2014 IEEE 3rd International Conference on
  • Conference_Location
    Luxembourg
  • Type

    conf

  • DOI
    10.1109/CloudNet.2014.6968968
  • Filename
    6968968