Awesome Open Source
Awesome Open Source

Supervised learning methods for biometric authentication on mobile devices

Valerie Ding [email protected]

Stephanie Dong [email protected]

Jonathan Li [email protected]

We develop fraud detection and user authentication classifiers for mobile keystroke and haptic patterns, achieving 84% accuracy, 90% recall, and 81% precision within one model architecture, and 99% recall and 83% across all models. In addition to proposing these models that outperform existing touch dynamics authentication models, we present a secure, space-efficient, and extensible framework for real-time biometric backlogging comparison.

Complete collaborative repo:

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