• DocumentCode
    251808
  • Title

    AMAD: Resource Consumption Profile-Aware Attack Detection in IaaS Cloud

  • Author

    Lazri, Kahina ; Laniepce, Sylvie ; Haiming Zheng ; Ben-Othman, Jalel

  • Author_Institution
    Security Dept., Orange Labs., Caen, France
  • fYear
    2014
  • fDate
    8-11 Dec. 2014
  • Firstpage
    379
  • Lastpage
    386
  • Abstract
    Cloud infrastructures are prone to various anomalies due to their ever-growing complexity and dynamics. Monitoring behavior of dynamic resource management systems is necessary to guarantee cloud reliability. In this paper, we present AMAD, a system designed for detecting an abusive use of dynamic virtual machine migration, in the case of the abusive virtual machine migration attack. This attack is performed by malicious manipulation of the amounts of resources consumed by Virtual Machines (VMs). AMAD identifies the VMs possibly at the origin of the attack by analyzing resource consumption profiles of the VMs to detect the fluctuating and highly correlated ones. We have implemented AMAD on top of the VMware ESXi platform and evaluated it both on our lab platform and under real cloud configurations. Our results show that AMAD pinpoints the attacking VMs which were intentionally injected in our experimentations, with high accuracy.
  • Keywords
    cloud computing; resource allocation; security of data; virtual machines; AMAD system; IaaS cloud infrastructure; VM; VMware ESXi platform; cloud configuration; cloud reliability; dynamic resource management systems; dynamic virtual machine migration; infrastructure-as-a-service; resource consumption profile-aware attack detection; resource consumption profiles; virtual machines; Accuracy; Dynamic scheduling; Indexes; Measurement; Memory management; Resource management; Vectors; Anomaly detection; Dynamic resource management; Reliability; Security; VM migration; VM profiling;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Utility and Cloud Computing (UCC), 2014 IEEE/ACM 7th International Conference on
  • Conference_Location
    London
  • Type

    conf

  • DOI
    10.1109/UCC.2014.48
  • Filename
    7027515