In this paper, we demonstrate a new way to perform continuous authentication using Mouse Dynamics as the behavioural biometric modality. In the proposed scheme, the user will be authenticated per mouse event performed on his/her system. We have used a publicly available mouse dynamics dataset and extracted per event features suitable for the proposed scheme. In this research, we have used the mouse dynamics data of 49 users and evaluated the system performance with 6 machine learning algorithms. In this approach, the genuine user has never been classified as an impostor throughout a full session whereas the average number of mouse actions an impostor could perform before detection is 94 from the best classification algorithm with a person based threshold.