StrokePIN: Enhancing PIN Authentication With Keystroke Dynamics for Mobile Devices
Summary
StrokePIN is an authentication system that uses keystroke dynamics (the unique way a person types, including timing and pressure patterns) combined with other data types to verify users' PIN (personal identification number) entries on mobile devices. The system uses a few-shot learning technique called Siamese Network (a machine learning approach that learns from very few examples) to work efficiently without needing to retrain constantly, and it includes security analysis showing that keystroke dynamics can provide meaningful protection against guessing attacks.
Solution / Mitigation
StrokePIN dynamically updates the template library (the stored reference patterns of how each user types) to mitigate the impact of user behavior drift over time, achieving a False Acceptance Rate of 8.3% and False Rejection Rate of 0.4%.
Classification
Original source: http://ieeexplore.ieee.org/document/11410089
First tracked: May 14, 2026 at 08:01 PM
Classified by LLM (prompt v3) · confidence: 92%