Biometric authentication has been getting widespread attention over the past decade with growing demands in automated secured personal identification and has been employed in diverse fields. It ensures actual presence of biometric entity of a person in contrast to a fake self-manufactured synthetic or reconstructed sample is a significant problem. Also in the previous work they use face and dress color as hard and soft biometric traits. The major drawback of the existing continuous authentication system is, it is able to successfully authenticate the user continuously with high tolerance to the user posture. So, to overcome this drawback and improve the systems robustness against illumination changes and cluttered background, in this paper we use additional biometric traits which are mole, ornament details and face dimensions in addition to the dress color and face color. Also, we extend it to the online exam application. That is, continuously monitoring of a person in an online exam is proposed employing hard biometric like facial recognition and soft biometrics. Modified PCA (Principal Component Analysis) is employed here for the facial recognition part. Both the hard biometric (face) and soft biometrics is fused with the help of optimization algorithm based similarity technique. Finally the authentication is performed and evaluated using standard evaluation metrics. The technique is implemented in MATLAB and will be compared to prominent existing techniques.