This document proposes a novel method for user identity verification using mouse signature. It captures mouse events such as mouse movements, clicks, and silences during a user's interaction with a canvas application. Features are extracted from these events to create a unique mouse signature for the user, which is stored in a database. When a user logs in, their current mouse signature is generated and compared to the stored signature to verify their identity. If the signatures match above a threshold like 80%, the user is authenticated. This adds an additional layer of security beyond just usernames and passwords. The system was designed to be more accurate than existing histogram-based approaches by verifying each individual mouse action.