Research Article
Password Authentication Using Context-Sensitive Associative Memory Neural Networks: A Novel Approach
334 downloads
@INPROCEEDINGS{10.1007/978-3-642-27308-7_49, author={P. Prasad and B. Prasad and A. Chakravarthy and P. Avadhani}, title={Password Authentication Using Context-Sensitive Associative Memory Neural Networks: A Novel Approach}, proceedings={Advances in Computer Science and Information Technology. Computer Science and Engineering. Second International Conference, CCSIT 2012, Bangalore, India, January 2-4, 2012. Proceedings, Part II}, proceedings_a={CCSIT PATR II}, year={2012}, month={11}, keywords={Password Authentication Cryptography Associaitive neural memory Kronecker Product context-sensitive memory models}, doi={10.1007/978-3-642-27308-7_49} }- P. Prasad
B. Prasad
A. Chakravarthy
P. Avadhani
Year: 2012
Password Authentication Using Context-Sensitive Associative Memory Neural Networks: A Novel Approach
CCSIT PATR II
Springer
DOI: 10.1007/978-3-642-27308-7_49
Abstract
Passwords are the most widely used form of authentication. In many systems the passwords, on the host itself, are not stored as plain text but are encrypted. However, conventional cryptography based encryption methods are having their own limitations, either in terms of complexity or in terms of efficiency. The conventional verification table approach has significant drawbacks and storing passwords in password table is one of the drawbacks.
Copyright © 2012–2024 ICST
