An Advanced Knowledge Based Graphical Authentication Framework with Guaranteed Confidentiality and Integrity

Abstract

The information and security systems largely rely on passwords,which remain the fundamental part of any authentication process. The conventional authentication method based on alphanumerical username and password suffer from significant disadvantages. The graphical password-based authentication system has recently been introduced as an effective alternative. Although the graphical schemes effectively generate the passwords with better flexibility and enhanced security, the most common problem with this is the shoulder surfing attack. This paper proposes an effective 3D graphical password authentication system to overcome such drawbacks. The system is based on the selection of click points for generating passwords. The proposed work involved a training phase for evaluating the model in terms of the success rate. The overall evaluations of the model in terms of password entropy, password space, login success rates, and prediction probability in the shoulder surfing and guessing attacks proved that the model is more confidential and maintains a higher range of integrity than the other existing models.