A Novel Approach for Pass Word Authentication using Brain -State -In -A Box (BSB) Model

TL;DR

This paper introduces a Brain-State-In-A-Box based method for password authentication that converts text and graphical passwords into probabilistic values, offering improved accuracy and faster response times over existing neural network techniques.

Contribution

The paper proposes a novel Brain-State-In-A-Box scheme for textual and graphical password authentication, enhancing accuracy and response speed compared to prior neural network methods.

Findings

Better accuracy in password authentication.

Quicker response time for registration and password changes.

Effective conversion of passwords into probabilistic values.

Abstract

Authentication is the act of confirming the truth of an attribute of a datum or entity. This might involve confirming the identity of a person, tracing the origins of an artefact, ensuring that a product is what it's packaging and labelling claims to be, or assuring that a computer program is a trusted one. The authentication of information can pose special problems (especially man-in-the-middle attacks), and is often wrapped up with authenticating identity. Password authentication using Brain-State -In-A Box is presented in this paper. Here in this paper we discuss Brain-State -In-A Box Scheme for Textual and graphical passwords which will be converted in to probabilistic values Password. We observe how to get password authentication Probabilistic values for Text and Graphical image. This study proposes the use of a Brain-State -In-A Box technique for password authentication. In comparison to existing layered neural network techniques, the proposed method provides better accuracy and quicker response time to registration and password changes.