• DocumentCode
    3527813
  • Title

    An Efficient Elliptic Curve Digital Signature Algorithm (ECDSA)

  • Author

    Lamba, Shweta ; Sharma, Mukesh

  • Author_Institution
    Comput. Sci. Dept., Technol. Inst. of Textile & Sci., Bhiwani, India
  • fYear
    2013
  • fDate
    21-23 Dec. 2013
  • Firstpage
    179
  • Lastpage
    183
  • Abstract
    In recent years, Elliptic Curve Cryptography (ECC) has attracted the attention of researchers and product developers because of its robust mathematical structure and highest security in comparison to other existing algorithms like RSA (Rivest Adleman and Shameer Public key Algorithm). Elliptic Curve Digital signature represents one of the most widely used security technologies for ensuring un-forge-ability and non-repudiation of digital data. Its performance heavily depends on an operation called point multiplication. Furthermore, root cause of security breakdown of ECDSA is that it shares three points of the elliptic curve public ally which makes it feasible for an adversary to gauge the private key of the signer. In this paper we proposed a new ECDSA which involves not as much of point multiplication operations as in existing ECDSA and shares only two curve points with everyone. The proposed method also reduces the point addition and point doubling operations. It is found to be more secure in contrast to existing ECDSA.
  • Keywords
    digital signatures; public key cryptography; ECC; ECDSA; RSA algorithm; Rivest Shamir Adleman public key algorithm; digital data nonrepudiation; digital data unforgeability; elliptic curve cryptography; elliptic curve digital signature algorithm; elliptic curve public ally; point addition operation; point doubling operation; point multiplication operation; security technology; Digital signatures; Elliptic curve cryptography; Elliptic curves; Equations; Handwriting recognition; ECC; ECDSA; Point Addition; Point multiplication; Signature generation; Signature verification;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Machine Intelligence and Research Advancement (ICMIRA), 2013 International Conference on
  • Conference_Location
    Katra
  • Type

    conf

  • DOI
    10.1109/ICMIRA.2013.41
  • Filename
    6918818