• DocumentCode
    2084837
  • Title

    On countermeasures to traffic analysis attacks

  • Author

    Fu, Xinwen ; Graham, Bryan ; Bettati, Riccardo ; Zhao, Wei

  • Author_Institution
    Dept. of Comput. Sci., Texas A&M Univ., College Station, TX, USA
  • fYear
    2003
  • fDate
    18-20 June 2003
  • Firstpage
    188
  • Lastpage
    195
  • Abstract
    We make three contributions. First, we propose Shannon´s perfect secrecy theory as a foundation for developing countermeasures to traffic analysis attacks on information security systems. A system violating the perfect secrecy conditions can leak mission critical information. Second, we suggest statistical pattern recognition as a fundamental technology to test an information system´s security. This technology can cover a large category of testing approaches because of statistical pattern recognition´s maturity and abundant techniques. Third, researchers have proposed traffic padding as countermeasures to traffic analysis attacks. By applying the proposed information assurance testing framework, we find that constant rate traffic padding does not satisfy Shannon´s perfect secrecy conditions because of its implementation mechanism. We design a variant rate traffic padding strategy as an alternative, which is validated by both theoretical analysis and empirical results.
  • Keywords
    computer crime; data privacy; information theory; internetworking; statistical analysis; telecommunication security; telecommunication traffic; Shannon perfect secrecy theory; constant rate traffic padding; information assurance testing framework; information security systems; mission critical information; statistical pattern recognition; traffic analysis attacks; variant rate traffic padding; Computer science; Contracts; Cryptography; Information analysis; Information security; Mission critical systems; Pattern recognition; Payloads; Protection; System testing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Assurance Workshop, 2003. IEEE Systems, Man and Cybernetics Society
  • Print_ISBN
    0-7803-7808-3
  • Type

    conf

  • DOI
    10.1109/SMCSIA.2003.1232420
  • Filename
    1232420