Title :
Weaknesses and drawbacks of a password authentication scheme using neural networks for multiserver architecture
Author_Institution :
Dept. of Comput. Sci. & Inf. Eng., Fu Jen Catholic Univ., Taipei, Taiwan
fDate :
7/1/2005 12:00:00 AM
Abstract :
In 2001, Li et al. proposed a password authentication scheme for the multiserver architecture by using a pattern classification system based on neural networks. Herein, we demonstrate that Li et al.´s scheme is vulnerable to an offline password guessing attack and a privileged insider´s attack, and is not reparable. Additionally, we show that Li et al.´s scheme has several drawbacks in practice.
Keywords :
computer networks; message authentication; neural nets; pattern classification; multiserver architecture; neural network; offline password guessing attack; password authentication scheme; pattern classification system; Artificial neural networks; Authentication; Computer science; Councils; Forgery; Network servers; Neural networks; Pattern classification; Public key; Smart cards; Multiserver architecture; neural networks; offline password guessing attack; password authentication; smart card; Algorithms; Computer Security; Computer Simulation; Models, Statistical; Neural Networks (Computer);
Journal_Title :
Neural Networks, IEEE Transactions on
DOI :
10.1109/TNN.2005.849781