Yingguang Lu

State Nuclear Power Technology Company (China)

Papers

Total Citations

H-Index

About

Yingguang Lu is a researcher whose work lies at the intersection of artificial intelligence, cybersecurity, and human–computer interaction, with a particular focus on CAPTCHA recognition and design. His most-cited paper, "A Transformer Network for CAPTCHA Recognition" (2021), introduces a novel application of transformer architectures to the challenging task of distinguishing human users from automated bots. By demonstrating that advanced deep learning models can effectively crack existing CAPTCHA systems, Lu’s work serves a dual purpose: it exposes vulnerabilities in current web security measures and provides a benchmark for developing more robust, AI-resistant CAPTCHA designs. This research is critical for improving website security and preventing harmful Internet attacks, as it directly informs the iterative cycle between CAPTCHA creation and recognition. Although his citation count is modest, Lu’s contributions are significant for practitioners and researchers working on adversarial machine learning and web authentication. His findings underscore the urgent need for CAPTCHA systems that can withstand increasingly sophisticated transformer-based attacks, making his work a valuable reference for anyone seeking to understand the evolving arms race between security designers and automated adversaries.