Papers
1
Total Citations
14
H-Index
1
About
Dr. Hongjing Li is a leading researcher at the intersection of cybersecurity, federated learning, and the Internet of Robotic Things (IoRT). Her work focuses on safeguarding distributed intelligence in heterogeneous, cross-silo environments, where robotic systems and industrial cobots collaborate under stringent privacy constraints. Her most-cited paper, "Safeguarding Privacy and Integrity of Federated Learning in Heterogeneous Cross-Silo IoRT Environments: A Moving Target Defense Approach" (2024, 14 citations), introduces an innovative moving target defense strategy to protect federated learning from adversarial attacks while preserving data integrity and model utility. This contribution is pivotal as IoRT expands, demanding robust, privacy-preserving frameworks for massive robotic networks. Dr. Li’s research addresses critical challenges in real-world deployments, balancing security, efficiency, and scalability. Her work is highly relevant for students and researchers exploring secure machine learning in cyber-physical systems, and her growing citation record underscores its timely impact on both academia and industry.
Research Focus
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Top Papers
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