• DocumentCode
    610862
  • Title

    Fault Detection in RNS Montgomery Modular Multiplication

  • Author

    Bajard, J. ; Eynard, J. ; Gandino, F.

  • Author_Institution
    LIP6, Univ. Pierre et Marie Curie Paris, Paris, France
  • fYear
    2013
  • fDate
    7-10 April 2013
  • Firstpage
    119
  • Lastpage
    126
  • Abstract
    Recent studies have demonstrated the importance of protecting the hardware implementations of cryptographic functions against side channel and fault attacks. In last years, very efficient implementations of modular arithmetic have been done in RNS (RSA, ECC, pairings) as well on FPGA as on GPU. Thus the protection of RNS Montgomery modular multiplication is a crucial issue. For that purpose, some techniques have been proposed to protect this RNS operation against side channel analysis. Nevertheless, there are still no effective and generic approaches for the detection of fault injection, which would be additionnally compatible with a leak resistant arithmetic. This paper proposes a new RNS Montgomery multiplication algorithm with fault detection capability. A mathematical analysis demonstrates the validity of the proposed approach. Moreover, an architecture that implements the proposed algorithm is presented. A comparative analysis shows that the introduction of the proposed fault detection technique requires only a limited increase in area.
  • Keywords
    cryptography; fault diagnosis; field programmable gate arrays; residue number systems; FPGA; GPU; RNS; RNS Montgomery modular multiplication; cryptographic functions; fault attacks; fault detection; fault injection; leak resistant arithmetic; modular arithmetic; side channel attacks; Computer architecture; Cryptography; Fault detection; Hardware; Redundancy; Resistance; Standards; Base Conversions; Fault Detection; Montgomery Reduction; Residue Number System;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Arithmetic (ARITH), 2013 21st IEEE Symposium on
  • Conference_Location
    Austin, TX
  • ISSN
    1063-6889
  • Print_ISBN
    978-1-4673-5644-2
  • Type

    conf

  • DOI
    10.1109/ARITH.2013.31
  • Filename
    6545899