Gaurrav7Yadav/Continuous-Authentication-using-behavioral-biometrics

The project is a personal or academic experiment with minimal traction (1 star, 0 forks) and no recent activity (velocity 0.0). Keystroke dynamics is a well-established field in cybersecurity research, and this repository represents a standard implementation of known machine learning patterns for biometric classification. There is no technical moat or unique dataset that would prevent it from being easily replicated. From a competitive standpoint, behavioral biometrics is a feature rather than a standalone product in the modern enterprise landscape. Major Identity and Access Management (IAM) providers like Microsoft (Entra ID), Okta, and Google (BeyondCorp) already integrate behavioral signals (including typing, mouse movement, and device telemetry) into their risk-based authentication engines. Furthermore, specialized vendors like TypingDNA and BioCatch have already established significant patent portfolios and data-driven moats in this specific niche. Given the age of the project and lack of community engagement, it is highly likely to remain a dormant reference implementation rather than a viable tool.