Amr Abdussalam

University of Science and Technology of China

Papers

Total Citations

H-Index

About

Amr Abdussalam is a researcher advancing the field of cybersecurity through deep learning-based CAPTCHA recognition. His primary research areas include computer vision, deep learning, and web security, with a specific focus on developing intelligent systems capable of deciphering text-based CAPTCHAs designed to distinguish humans from bots. His most cited work, "CAPTCHA Recognition Using Deep Learning with Attached Binary Images" (2020), has garnered 40 citations and addresses the critical challenge of enhancing website security by creating algorithms that can accurately interpret distorted text, thereby exposing vulnerabilities in existing CAPTCHA systems. Building on this, his 2023 paper "Deep Learning Based CAPTCHA Recognition Network with Grouping Strategy" (12 citations) introduces a novel grouping strategy to improve recognition accuracy and efficiency. Abdussalam's contributions are notable for their practical implications in cybersecurity, helping to identify weaknesses in widely-used verification mechanisms and informing the development of more robust defenses. His work bridges the gap between machine learning theory and real-world security applications, making him a key voice in the ongoing battle against automated Internet attacks.