VC-DETR: A VGG-CNN-Detection Transformer Model Based Blockchain Secure Iris Detection
Sirui Wang, Tengyue Wu, Junhan Li, Lei Zhang · 2024
With the rapid development of information technology, data has become a vital asset in modern society. With its distributed, immutable and encrypted characteristics, blockchain technology has become a powerful tool for data security and privacy protection. Therefore, identity authentication has always been crucial in ensuring transaction security and data integrity. In blockchain systems, iris recognition provides strong authentication and enhances security by ensuring that only verified individuals can conduct transactions or access sensitive data. This paper proposes an innovative iris detection method based on the blockchain identity authentication platform, VGG-CNN-Detection Transformer (VC-DETR). The method improves iris detection accuracy and precisely locates the pupil center. Experimental analysis is performed using the CASIA-1000 dataset. The experiment shows VC-DETR model outperforms the conventional model to demonstrate its potential for real-world applications. By combining iris recognition technology with the blockchain platform, this approach achieves dual identity authentication and provides an additional encryption layer for the security of the blockchain system.