A Novel Approach For Authenticating Textual Or Graphical Passwords Using Hopfield Neural Network

Abstract

ABSTRACT

Performance Evaluation of Password Authentication using Associative Neural Memory Models

“…Password authentication is a common approach to the system security and it is also a very important procedure to gain access to user resources. In the conventional password authentication methods a server has to authenticate the legitimate user [1].…”

“…Our preliminary analysis suggests that it is more difficult to break graphical passwords using the traditional attack methods such as brute force search, dictionary attack, or spyware. However, since there is not yet wide deployment of graphical password systems, the vulnerabilities of graphical passwords are still not fully understood [1]. Graphical password schemes have been proposed as a possible alternative to text-based schemes, motivated partially by the fact that humans can remember pictures better than text; psychological studies supports such assumption .…”

A Novel Soft Computing Authentication Scheme for Textual and Graphical Passwords

“…Even if the information is stored in the hashed format [9] or encrypted format the intruder can affect the system like appending the wrong password for an identified user etc. hence to overcome this setback we use soft computing approach, a neural network with Back Propagation Learning [12]. In this work we explained different password mechanisms and different stages of password enhancements, drawbacks of each mechanism.…”

“…In our scheme users are allowed to give a username and password at the registration phase without any password policies, we developed a Feed Forward Neural Network which takes the user name as an input and produces user password which was given at the registration as output [12]. We employed Back propagation [13] a supervised learning algorithm s. The weights of the neural network are stored at the sever side DB [4,12].…”

“…We employed Back propagation [13] a supervised learning algorithm s. The weights of the neural network are stored at the sever side DB [4,12]. Hence every time the user logs in he provides his/her username, this username is sent to server, and then server gives the username as input to the FFNN with the stored weights as weights of the neural network therefore providing the password of the user.…”