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