Title :
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
fDate :
11/1/2001 12:00:00 AM
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;
Journal_Title :
Neural Networks, IEEE Transactions on
