A Novel Approach for Password Authentication Using Bidirectional Associative Memory

Password authentication is a very important system security procedure to gain access to user resources. In the Traditional password authentication methods a server has check the authenticity of the users. In our proposed method users can freely select their passwords from a predefined character set. They can also use a graphical image as password. The password may be a character or an image it will be converted into binary form and the binary values will be normalized. Associative memories have been used recently for password authentication in order to overcome drawbacks of the traditional password authentication methods. In this paper we proposed a method using Bidirectional Associative Memory algorithm for both alphanumeric (Text) and graphical password. By doing so the amount of security what we provide for the user can be enhanced. This paper along with test results show that converting user password in to Probabilistic values and giving them as input for BAM improves the security of the system

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

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.