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
Link To Document :
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