A remote password authentication scheme for multiserver architecture using neural networks

Author

Li, Li-Hua ; Lin, Iuon-Chang ; Hwang, Min-Shiang

Author_Institution

Dept. of Inf. Manage., Chaoyang University of Technology, Taichung, Taiwan

Volume

12

Issue

6

fYear

2001

fDate

11/1/2001 12:00:00 AM

Firstpage

1498

Lastpage

1504

Abstract

Conventional remote password authentication schemes allow a serviceable server to authenticate the legitimacy of a remote login user. However, these schemes are not used for multiserver architecture environments. We present a remote password authentication scheme for multiserver environments. The password authentication system is a pattern classification system based on an artificial neural network. In this scheme, the users only remember user identity and password numbers to log in to various servers. Users can freely choose their password. Furthermore, the system is not required to maintain a verification table and can withstand the replay attack

Keywords

learning (artificial intelligence); message authentication; neural net architecture; pattern classification; computer security; legitimacy; multiserver architecture; neural networks; pattern classification system; remote login user; remote password authentication scheme; replay attack; Artificial neural networks; Authentication; Computer architecture; Computer security; Control systems; Information security; Network servers; Neural networks; Pattern classification; Privacy;

fLanguage

English

Journal_Title

Neural Networks, IEEE Transactions on

Publisher

ieee

ISSN

1045-9227

Type

jour

DOI

10.1109/72.963786

Filename

963786