• DocumentCode
    2796870
  • Title

    Improvement of power analysis attacks using Kalman filter

  • Author

    Souissi, Youssef ; Guilley, Sylvain ; Danger, Jean-Luc ; Mekki, Sami ; Duc, Guillaume

  • Author_Institution
    Dept. ComElec, Inst. Telecom/Telecom-ParisTech, Paris, France
  • fYear
    2010
  • fDate
    14-19 March 2010
  • Firstpage
    1778
  • Lastpage
    1781
  • Abstract
    Power analysis attacks are non intrusive and easily mounted. As a consequence, there is a growing interest in efficient implementation of these attacks against block cipher algorithms such as Data Encryption Standard (DES) and Advanced Encryption Standard (AES). In our paper we propose a new technique based on the Kalman theory. We show how this technique could be useful for the cryptographic domain by making power analysis attacks faster. Moreover we prove that the Kalman filter is more powerful than the High Order Statistics technique.
  • Keywords
    Kalman filters; cryptography; telecommunication security; Kalman filter; advanced encryption standard; block cipher algorithms; data encryption standard; power analysis attacks; Algorithm design and analysis; Biomedical measurements; Cryptography; Energy consumption; Kalman filters; Signal analysis; Signal processing algorithms; State-space methods; Statistics; Telecommunications; High Order Statistics; Kalman filtering; power analysis attacks (SPA, DPA, CPA); symmetrical encryption (AES, DES);
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Acoustics Speech and Signal Processing (ICASSP), 2010 IEEE International Conference on
  • Conference_Location
    Dallas, TX
  • ISSN
    1520-6149
  • Print_ISBN
    978-1-4244-4295-9
  • Electronic_ISBN
    1520-6149
  • Type

    conf

  • DOI
    10.1109/ICASSP.2010.5495428
  • Filename
    5495428