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Authentication Scheme for Multi-Server Environment

R. Ganesan, Dr. A. Arul Lawrence Selvakumar

Abstract


Conventional authentication schemes allow a serviceable server to authenticate the legitimacy of a remote login user. However, these schemes are not used for multi-server architecture environments. This paper presents a secure and efficient remote user authentication scheme for multi-server environments. This user authentication scheme is a pattern classification system based on an artificial neural network. In this scheme, the users only remember user identity and password 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


Neural Network, Multi Server Architecture, User Authentication, Remote login, Security.

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References


A. S. Anagun and I. Cin, “A neural-network-based computer access security system for multiple users,” in Proc. 23rd Int. Conf. Comput. Ind. Eng., vol. 35, 1998, pp. 351–354.

R. K. Bauer, T. A. Berson, and R. J. Feiertag, “A key distribution protocol using event markers,” ACM Trans. Comput. Syst., vol.1, pp. 249–255, 1983.

S. Bleha and M. S. Obaidat, “Dimensionality reduction and feature extraction applications in identifying computer users,” IEEE Trans. Syst., Man, Cybern., vol. 21, pp. 452–456, Mar. /Apr. 1991.

C. C. Chang, S. M. Tsu, and C. Y. Chen, “Remote scheme for password authentication based on theory of quadratic residues,” Comput. Commun. vol. 18, pp. 936–942, Dec. 1995.

Li-Hua Li, Chang Lin and Hwang, “A Remote Password Authentication Scheme for MultiServer Architecture Using Neural Networks”, IEEE Transactions on Neural Networks, 2001

Shahbaz Zahr Reyhani and Mehregan Mahdavi “User Authentication Using Neural Network in Smart Home Networks”, International Journal of Smart Home, 2007


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