• DocumentCode
    1922470
  • Title

    An approach with two-stage mode to detect cache-based side channel attacks

  • Author

    Si Yu ; Xiaolin Gui ; Jiancai Lin

  • Author_Institution
    Shaanxi Province Key Lab. of Comput. Network, Xi´an Jiaotong Univ., Xi´an, China
  • fYear
    2013
  • fDate
    28-30 Jan. 2013
  • Firstpage
    186
  • Lastpage
    191
  • Abstract
    Side channel attacks, which intend to analyze third party sharing resources responses, has become a significant security threat to cloud, in particular the cache-based side channel attacks. In this paper, to eliminate such a security threat in cloud, based on the observation that the creation of a side channel has certain effects on the resource utilization in both the host and guest, we investigate the detection approach for detecting cache-based side channel attacks, named CSDA. The approach uses the two-stage detection mode which consists of host detection and guest detection, combines shape test and regularity test to extract the attack features from hosts and guests, and uses pattern recognition techniques to distinguish the attack VMs from the legitimate VMs. At last, a series of experiments are conducted, and the experimental results show that CSDA is capable of detecting them in cloud effectively.
  • Keywords
    cloud computing; resource allocation; telecommunication channels; telecommunication security; CSDA; cache-based side channel attacks; cloud computing; guest detection; host detection; pattern recognition; regularity test; resource utilization; security threat; shape test; third party sharing resources responses; two-stage detection mode; two-stage mode; Cloud computing; Feature extraction; Security; Shape; Standards; Synthetic aperture sonar; Timing; attack detection; cache-based side channel attacks; cloud computing; virtualization security;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Networking (ICOIN), 2013 International Conference on
  • Conference_Location
    Bangkok
  • ISSN
    1976-7684
  • Print_ISBN
    978-1-4673-5740-1
  • Electronic_ISBN
    1976-7684
  • Type

    conf

  • DOI
    10.1109/ICOIN.2013.6496374
  • Filename
    6496374