Development of the Decentralized Biometric Identity Verification System Using Blockchain Technology and Computer Vision
G. Uteyev, R. F. Gibadullin
Abstract
This article investigates the creation of a decentralized system for biometric-based identity verification, integrating blockchain technology and computer vision. The goal is to provide a secure verification method, minimizing identity fraud and transactional deceptions. The system combines facial recognition, fingerprint scanning, and iris scanning, ensuring precise individual identification. Blockchain guarantees data immutability and decentralization, ensuring biometric data integrity. Computer vision enhances biometric data processing, improving system accuracy and efficiency. Key components include blockchain for secure biometric data storage via Solidity-based smart contracts, computer vision algorithms like convolutional neural networks for facial image analysis, and the OpenPGP library for asymmetric encryption. The system's backend is developed in Python using FastAPI, with a React-based frontend for user interaction. This web application is compatible with modern browsers and integrates seamlessly with existing systems. Results show the development of a novel blockchain-based decentralized identity system, employing a Solidity smart contract for encrypted biometric data storage and a React and FastAPI web application for facial image analysis. The system ensures data privacy through asymmetric encryption and has undergone extensive testing, proving significant advantages over conventional solutions. The discussion emphasizes the system's benefits in secure, efficient, and accurate identity verification, suitable for various sectors like finance, healthcare, and government services. The system's future could involve expanding biometric modalities, algorithmic optimization, and incorporating emerging technologies like the Internet of Things.