Papers
1
Total Citations
11
H-Index
1
About
Zigang Cao is a leading researcher in cybersecurity, specializing in the detection of malicious automated threats—particularly advanced web robots and cloud-based bots—using machine learning and network traffic analysis. His most-cited work, "Machine Learning Based CloudBot Detection Using Multi-Layer Traffic Statistics" (2019, 11 citations), addresses the growing menace of sophisticated bots used in underground economies for click fraud, fake account registration, and other fraudulent activities that harm e-commerce and online services. Cao’s key contribution lies in developing multi-layer traffic analysis techniques that extract statistical features from network flows, enabling robust detection of evasive cloud-hosted bots. By combining machine learning with deep packet inspection, his research provides practical defenses against automated attacks that bypass traditional security measures. His work has significant implications for protecting digital business ecosystems, and he continues to advance the field through innovative approaches to botnet and fraud detection. With a focus on real-world impact, Cao’s research helps secure online transactions and user trust in an era of increasingly sophisticated cyber threats.
Research Focus
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Top Papers
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