Abstract

The article proposes a new method for user recognition based on their unique eyelid blinking pattern. In our study, we utilized the publicly available mEBAL database and the data we collected. The temporal eyelid movement patterns extracted from the samples in the database are analyzed by a siamese neural network. Our research aimed to develop a method that is resistant to shoulder surfing and brute force attacks, while also not requiring complex recording devices. Most user authentication methods utilizing eyelid blinking patterns are vulnerable to pattern replication attacks. The achieved results of 98.20% accuracy and 0.11 EER unequivocally demonstrate the superiority of the proposed method over other methods using eyelid blinking for user authentication.

Recommended Citation

Malinowski, K., Saeed, K. & Sawicki, A.(2026). Siamese neural network based algorithm for user recognition by their eye blinking. In M. Valenta, B. Mannová, R. Pergl, A. Przybylek, M. Lang, H. Linger, C. Schneider, N. Iivari, & E. Insfran (Eds.), Making ISD Sustainable: Reloaded with AI and Automation (ISD2026 Proceedings). Prague, Czech Republic: Czech Technical University in Prague. ISBN: 978-80-01-07585-2. https://doi.org/10.62036/ISD.2026.203

Paper Type

Poster

DOI

10.62036/ISD.2026.203

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Siamese neural network based algorithm for user recognition by their eye blinking

The article proposes a new method for user recognition based on their unique eyelid blinking pattern. In our study, we utilized the publicly available mEBAL database and the data we collected. The temporal eyelid movement patterns extracted from the samples in the database are analyzed by a siamese neural network. Our research aimed to develop a method that is resistant to shoulder surfing and brute force attacks, while also not requiring complex recording devices. Most user authentication methods utilizing eyelid blinking patterns are vulnerable to pattern replication attacks. The achieved results of 98.20% accuracy and 0.11 EER unequivocally demonstrate the superiority of the proposed method over other methods using eyelid blinking for user authentication.