SecureRhythm: Continuous Behavioral Biometric Authentication

SecureRhythm is a continuous behavioral biometric authentication system intended for session-based identity assurance in contemporary digital systems. Traditional biometric and behavioral-based authentication systems are typically based on the verification of users’ identities during the login process. On the other hand, SecureRhythm continuously verifies the patterns of user behavior throughout the entire session. For instance, the system uses behavioral biometrics such as keystroke dwell time, flight time, typing rhythm, correction behavior, cursor movement, and navigation behavior. The system uses deep learning-based approaches such as Convolutional Neural Networks (CNN), Bi-Directional Long Short-Term Memory (Bi-LSTM), and ensemble-based approaches for behavioral classification and anomaly detection. In addition, the system uses an adaptive risk scoring engine for the entire system. Experimental validation of the proposed system shows improved stability in the recognition of behavioral biometrics for Top-1, Top-3, and Top-5 accuracy levels. The proposed system is privacy-preserving and has the capability for governance awareness.