Abstract
In the digital world, ensuring biometric template security is critical, yet many existing methods prioritize efficiency over protection, leaving sensitive data vulnerable. To address this gap, we propose a robust and efficient approach for securing online signature templates without compromising performance. Our method transforms online signature features into quantized feature vectors encoded as non-invertible binary bitstrings. A user-specific key ensures unique bitstrings per session, effectively preventing attacks. By converting signatures into fixed-length bitstrings, our approach enhances computational efficiency while preserving accuracy. Unlike existing methods, it does not rely on strict signature positioning, ensuring adaptability in real-world scenarios. Experimental evaluations on SVC 2004 (Task 2), xLongSignDB, eBioSignDS1, and MCYT-100 confirm its superior security, diversity, and revocability, meeting ISO/IEC 4745: 2022 standards.
| Original language | British English |
|---|---|
| Article number | 127646 |
| Journal | Expert Systems with Applications |
| Volume | 283 |
| DOIs | |
| State | Published - 15 Jul 2025 |
Keywords
- Authentication
- Biometrics
- Online signature
- Privacy
- Recognition
- Revocability
- Security
- User template