RETRACTED ARTICLE: Continuous user authentication based score level fusion with hybrid optimization

Abstract

With the fast growing demands in authentication biometric-based authentication system has been widely utilized in many applications which require secured personal identification/verification. In the existing computer systems, there is a possibility of an imposter gaining access when a user session is active and the user moves away from the system. To solve this problem, proposes a continuous user authentication scheme. Continuous authentication (CA) system verifies the user continuously once a person is logged in. CA system prevents the intruders from invoking the system. It passively verifies the system without interrupting the users work progress. In this paper, score level fusion is carried out using optimization that is genetic particle swarm optimization and classifiers lazy classifier—Naive Bayes held for recognition process. The main objective of the proposed method is to fuse the user biometric traits and to accomplish the optimal result in the continuous user authentication. The proposed technique consists of four modules, namely processing module, feature extraction module, fusion module and recognition module. Finally, the proposed fusion method is applied to remote biometric authentication. The implementation is carried out using MATLAB and the evaluation metrics employed are false acceptance rate, false rejection rate and accuracy, sensitivity and specificity. From the results, we can observe that the proposed technique has achieved better performance metrics values for continuous authentication process.