Keywhan Chung
Papers
2
Total Citations
21
H-Index
2
About
Keywhan Chung is a leading researcher at the intersection of cybersecurity, robotics, and adversarial machine learning. His work exposes critical vulnerabilities in autonomous and robotic systems, demonstrating how cyberattacks can exploit control data to compromise physical safety. In his highly cited 2019 study on the Raven-II surgical robot, Chung showed that smart malware could leverage leaked control data to manipulate robotic applications, a groundbreaking contribution that highlighted the urgent need for security in medical and industrial robotics. With over 20 citations across his most influential papers, his research has shaped how engineers think about the convergence of cyber threats and physical systems. Chung also explores the darker side of AI, warning that machine learning itself can be weaponized by malicious adversaries—a near-future scenario he argues is already becoming reality. His work is essential reading for anyone studying the security of cyber-physical systems, robotics, or adversarial AI, and it continues to inform both academic research and practical defense strategies in critical infrastructure protection.
Research Focus
Key Achievements
Top Papers
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