• DocumentCode
    2767262
  • Title

    Synthetic Biometrics: A Survey

  • Author

    Yanushkevich, S.N.

  • Author_Institution
    Calgary Univ., Calgary
  • fYear
    0
  • fDate
    0-0 0
  • Firstpage
    676
  • Lastpage
    683
  • Abstract
    This brief survey addresses the state-of-the-art techniques of inverse biometrics, which deals with synthesis of biometric data. It reports on genesis of synthetic biometric, advanced methods, and open application-specific problems. Currently deployed biometric systems use comprehensive methods and algorithms (such as pattern recognition, decision making, database searching, etc.) to analyze biometric data collected from individuals. We consider the inverse task, synthesis of artificial biometric data. These biologically meaningful data are useful, for example, for testing the biometric tools, and for enhancing the security of biometric systems. The synthetic data replicate all possible instances of otherwise unavailable data, thus, creating a variety of samples for testing. Properly created artificial biometric data provides a basis for enhancing security through the detailed and controlled modeling of a wide range of training skills, strategies and tactics of a hypothetical robber or forger. Databases of synthetic biometric data also serve for simulation in forensic systems.
  • Keywords
    biometrics (access control); security of data; database searching; decision making; forensic systems; inverse biometrics; inverse task; open application-specific problems; pattern recognition; security; synthetic biometrics; Algorithm design and analysis; Bioinformatics; Biometrics; Data analysis; Data security; Databases; Decision making; Pattern analysis; Pattern recognition; System testing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks, 2006. IJCNN '06. International Joint Conference on
  • Conference_Location
    Vancouver, BC
  • Print_ISBN
    0-7803-9490-9
  • Type

    conf

  • DOI
    10.1109/IJCNN.2006.246749
  • Filename
    1716160