Xing Wan

Papers

Total Citations

H-Index

About

Xing Wan is a researcher at the forefront of cybersecurity, with a primary focus on adversarial machine learning and the vulnerabilities of automated human verification systems. His most influential work, "A Review on Text-based CAPTCHA Breaking Based on Deep Learning Methods" (2023), has garnered 6 citations and stands as a critical synthesis of how deep learning techniques are systematically dismantling the security of text-based CAPTCHAs—a cornerstone of web protection against bots and crawlers. By analyzing state-of-the-art breaking methods, Wan highlights the escalating arms race between CAPTCHA designers and attackers, revealing profound implications for global cyberspace security. His contributions extend beyond mere review; they serve as a wake-up call for the development of more robust, AI-resistant verification systems. Through this work, Xing Wan has established himself as a key voice in understanding how modern AI threatens traditional security measures, making his research essential reading for students and professionals navigating the evolving landscape of digital defense.