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Continuous user authentication and anomaly detection using keystroke dynamics (behavioral biometrics) and Random Forest classifiers.
Defensibility
stars
3
The project is a classic academic or personal experiment with negligible market presence (3 stars, 0 forks) and has been dormant for nearly four years. It utilizes a standard Random Forest approach on a limited dataset of 51 users. The defensibility is near zero as the approach is a commodity implementation of a well-documented behavioral biometric technique. From a competitive standpoint, keystroke dynamics is an 'adjacent feature' rather than a standalone product category. Major OS and IAM (Identity and Access Management) vendors like Microsoft (Windows Hello), Apple, and Okta are the natural owners of this technology, as they have access to low-level hardware interrupts and much larger training datasets. Furthermore, the reliance on a 'fixed-text' password for the study limits its real-world utility compared to 'free-text' dynamics which allow for true continuous authentication regardless of what the user is typing. There is no technical moat or community engagement here that would prevent it from being immediately superseded by any modern enterprise security suite.
TECH STACK
INTEGRATION
reference_implementation
READINESS