Research Output
Behaviour reflects personality: detecting co-residence attacks on Xen-based cloud environments
  Cloud computing is gradually becoming the most popular option of Information Technology infrastructures. However, an important issue that has emerged through that revolution is the preservation of an adequate level of security for the infrastructure and the confrontation of malicious insiders. This paper proposes a methodology for detecting the co-residency attack in the kernel layer of a Xen-based cloud environment, using an implementation of the Smith–Waterman genetic algorithm. The proposed approach has been explored in a test bed environment, producing results that verify its effectiveness.

  • Type:

    Article

  • Date:

    08 August 2014

  • Publication Status:

    Published

  • Publisher

    Springer Nature

  • DOI:

    10.1007/s10207-014-0255-8

  • Cross Ref:

    255

  • ISSN:

    2356-5845

  • Library of Congress:

    QA75 Electronic computers. Computer science

  • Dewey Decimal Classification:

    005.8 Data security

  • Funders:

    Historic Funder (pre-Worktribe)

Citation

Pitropakis, N., Pikrakis, A., & Lambrinoudakis, C. (2015). Behaviour reflects personality: detecting co-residence attacks on Xen-based cloud environments. International Journal of Information Security, 14(4), 299-305. doi:10.1007/s10207-014-0255-8

Authors

Keywords

Cloud computing, Security, Malicious insider, Xen, System calls, Smith–Waterman,

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