Integrating Blockchain in Facial Recognition Systems.

Abstract

This project explores the integration of blockchain technology with facial recognition systems to address critical challenges in security, privacy, and data integrity. Traditional facial recognition systems often suffer from centralized vulnerabilities, such as data breaches and lack of user control. By leveraging blockchain's decentralized and immutable ledger, this project proposes a robust framework for secure biometric data management. The system combines deep learning models (e.g., FaceNet) for face detection and feature extraction with Ethereum smart contracts and IPFS for decentralized storage. Key outcomes include a functional prototype demonstrating tamper-proof identity verification, enhanced privacy through cryptographic hashing, and auditable transaction logs. The results validate the system's efficacy, achieving 95% accuracy in recognition tasks while mitigating risks associated with centralized databases. This work contributes to advancing secure, transparent, and scalable biometric systems for applications in healthcare, finance, and governance.