Qingyang Li
Papers
1
Total Citations
3
H-Index
1
About
Qingyang Li is a leading researcher in cybersecurity, with a specialized focus on the security of industrial robotic systems. Their work centers on developing novel frameworks to identify and mitigate vulnerabilities in critical infrastructure, particularly within the domain of industrial control systems (ICS) and the Internet of Things (IoT). Li’s major contribution is the creation of FuzzAGG, a fuzzing-driven attack graph generation framework for industrial robot systems, which systematically uncovers potential attack paths by combining automated testing with graph-based analysis. This innovative approach has garnered significant attention, with their most-cited paper, "FuzzAGG: A fuzzing-driven attack graph generation framework for industrial robot systems" (2024), already accumulating 3 citations shortly after publication—a strong indicator of its immediate impact on the field. By bridging the gap between theoretical security models and practical, real-world testing, Li’s work provides engineers and researchers with actionable tools to harden robotic systems against sophisticated cyber threats. Their research is vital for ensuring the safety and reliability of automated manufacturing, and they continue to push boundaries in proactive security assessment for emerging technologies.
Research Focus
Key Achievements
Top Papers
- 1