• DocumentCode
    2068066
  • Title

    Security software using neural networks

  • Author

    Zimmer, Jean Philippe ; Mitéran, Johel ; Yang, Fan ; Paindavoine, Michel

  • Author_Institution
    Bourgogne Univ., Dijon, France
  • Volume
    1
  • fYear
    1998
  • fDate
    31 Aug-4 Sep 1998
  • Firstpage
    72
  • Abstract
    This paper describes the structure and the theoretical principles of the security software that the authors have developed. This software is an industrial application based on neural networks theory. Its aim is to recognize somebody´s face and thus to add one more protection level to Windows NT and Windows 95 security access. They implemented the face learning phase by using projection onto an eigenvectors matrix and the backpropagation algorithm. They stored, in a database, the identification of the faces which have been learned and added a security protection when opening the personal session of the operating system Windows NT and created a new level of protection for Windows 95. They tested their algorithms on images of other types than faces and the results allow the use of the software in industrial control
  • Keywords
    backpropagation; eigenvalues and eigenfunctions; face recognition; neural nets; security of data; Windows 95; Windows NT; backpropagation algorithm; database storage; eigenvectors matrix; face learning; face recognition; industrial application; neural networks; security software; Application software; Backpropagation algorithms; Computer industry; Data security; Face recognition; Image databases; Neural networks; Operating systems; Protection; Software testing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Industrial Electronics Society, 1998. IECON '98. Proceedings of the 24th Annual Conference of the IEEE
  • Conference_Location
    Aachen
  • Print_ISBN
    0-7803-4503-7
  • Type

    conf

  • DOI
    10.1109/IECON.1998.723947
  • Filename
    723947