A Hybrid Biometric Approach for Secure Vaccination Status Verification

Abstract

Thisproject introducesaTransformer-BasedAI system for verifying vaccination status using face.Traditionalmethods like QR codes and paper certificates are prone to forgery and securityrisks.Vision Transformers (ViTs) replace CNNs for face recognition, improving accuracy and adaptability.Dual-layer authentication provides a seamless and fraud- proof process. The system is designed to be robust, secure, and user-friendly.

Introduction

Amid global pandemics and growing digital reliance, securely verifying vaccination status is a critical public health need. Traditional verification methods like physical vaccine cards and QR codes are prone to forgery, loss, and misuse. Biometric systems, which authenticate people using unique physical or behavioral traits, offer a more secure alternative. However, systems relying on a single biometric trait (unimodal) face challenges such as spoofing and environmental sensitivity.

To address these issues, a hybrid biometric system combining multiple biometric modalities (e.g., facial recognition and fingerprint) is proposed for reliable and tamper-resistant vaccination verification. This approach enhances security with features like liveness detection to prevent spoofing.

Current systems typically use face recognition linked to vaccination databases, OTP verification, or QR codes, with manual checks still common in some places. The proposed system integrates facial recognition and additional biometric traits to improve accuracy and user-friendliness, especially useful in healthcare settings, airports, and schools.

Implementation involves modules for user interface, image processing, and data management, leveraging machine learning algorithms like Support Vector Machines (SVM) for facial classification, OpenCV for image analysis, and automated report generation. The system workflow includes image capture, registration, verification, and generating downloadable reports to confirm vaccination status securely and efficiently.

Conclusion

The face recognition-based vaccination verification system provides a fast, secure, and contactless way to confirm vaccination status. verification offers a robust, reliable, and tamper-proof solution for modern identity and health record management. By integrating multiple biometric modalities such as fingerprint, facial recognition, and voice authentication the system significantly enhancesaccuracy, reducestheriskofspoofing, and ensures that vaccination data is accessed only by authorized individuals.

References

[1] Jain,A.K.,Ross,A.,&Nandakumar, K. (2011). Introduction to Biometrics. Springer Science & Business Media. [2] Ross,A.,Nandakumar,K.,&Jain,A.K. (2006). Handbook of Multibiometrics. Springer. [3] NIST. (2021). Biometric Standards, Performance & Interoperability. National Institute of Standards and Technology. [4] Kisku, D. R., Rattani,A., & Gupta, P. (2010). Multibiometric Systems: Models, Performance Evaluation, and Security. Springer.

Copyright

Copyright © 2025 Mrs. D. Urlamma, Ch. Chandana, P. Sunitha, M. Renuka, M. Lavanya. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.