DOI: 10.17587/prin.16.622-631

A System for Automating Biometric Authentication of a User based on the Results of an Analysis of the Dynamic Characteristics of his Handwritten Signature

E. S. Anisimova, Associate Professor, ellin_a@mail.ru, Elabuga Institute (branch) of the Kazan (Volga Region) Federal University, Elabuga,423600, Russian Federation

Corresponding author: Ellina S. Anisimova, Associate Professor, Elabuga Institute (branch) of the Kazan (Volga Region) Federal University, 423600, Elabuga, Russian Federation, E-mail: ellin_a@mail.ru

The article presents a hardware and software system developed by the author, which provides a procedure for biometric authentication of its users based on the dynamics of their handwritten signature. The apparatus of fuzzy logic and genetic algorithms is used to implement the procedure. The system analyzes dynamic signature characteristics, including pen coordinates, pressure, azimuth, and tilt angle. A key feature is the application of fuzzy logic to describe extracted features, accommodating the inherent uncertainty and variability in handwritten signatures. Furthermore, a genetic algorithm automates the selection of fuzzy rules and determines the optimal decision threshold, minimizing the Equal Error Rate. This approach adapts the system to individual handwriting characteristics, enhancing authentication accuracy and reliability. Experimental studies were conducted using the publicly available MCYT-Signature-100 data-set, comprising signatures from 100 different users, to evaluate the system's effectiveness. The results demonstrate a low Equal Error Rate of 0.28 %, outperforming several existing signature dynamics authentication systems. This achievement confirms the effectiveness of combining fuzzy logic and genetic algorithms for biometric verification. The system's modular architecture, encompassing signature input and processing, training, and decision-making subsystems, ensures flexibility and scalability, enabling adaptation to various application scenarios. The system is implemented using Scilab for signal processing and fuzzy logic implementation, and C++ for high-performance data acquisition from a graphics tablet via the Wintab API. The developed system holds significant potential for applications requiring robust authentication, such as e-commerce, banking, e-government, and access control. The low Equal Error Rate minimizes the risks of both false rejection of authorized users and unauthorized access by intruders, balancing security and usability. Future research will focus on exploring alternative optimization methods for further Equal Error Rate reduction and assessing system resilience to various attack types to develop effective protective mechanisms.

Keywords: biometric authentication, handwritten signature, genetic algorithm, fuzzy verification, feature extraction, performance evaluation, Scilab, C++, MCYT-Signature-100

pp. 622—631

For citation:
Anisimova E. S. A System for Automating Biometric Authentication of a User based on the Results of an Analysis of the Dynamic Characteristics of his Handwritten Signature, Programmnaya Ingeneria, 2025, vol. 16, no. 12, pp. 622—631. DOI: 10.17587/prin.16.622-631. (in Russian).

This work was supported by a grant from the Academy of Sciences of the Republic of Tatarstan, awarded to young PhD holders (postdoctoral researchers) for the purpose of defending doctoral dissertations, conducting research, and performing job duties in scientific and educational organizations of the Republic of Tatarstan within the framework of the State Program of the Republic of Tatarstan "Scientific and Technological Development of the Republic of Tatarstan".

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