Mingsheng Gao

Papers

Total Citations

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About

Mingsheng Gao is a researcher whose work lies at the intersection of cybersecurity and deep learning, with a particular focus on CAPTCHA recognition and adversarial machine learning. His most-cited paper, "CAPTCHA Recognition Using Deep Learning with Attached Binary Images" (2020, 40 citations), addresses a fundamental challenge in web security: distinguishing human users from automated bots. By developing deep learning models capable of breaking text-based CAPTCHAs—traditionally designed to be human-friendly but machine-resistant—Gao has contributed to a deeper understanding of the vulnerabilities in widely used security mechanisms. This work not only highlights the growing sophistication of AI-driven attacks but also informs the design of more robust CAPTCHA systems. Gao’s research is notable for bridging theoretical deep learning techniques with practical cybersecurity applications, offering insights that are valuable to both academic researchers and industry practitioners. His contributions underscore the ongoing arms race between security measures and adversarial AI, making his work essential reading for students and researchers interested in the future of web security and machine learning robustness.