Papers
1
Total Citations
11
H-Index
1
About
Gang Xiong is a cybersecurity researcher whose work focuses on network traffic analysis, bot detection, and the security challenges posed by automated malicious actors in digital ecosystems. His research addresses the growing threat of sophisticated web robots — commonly known as CloudBots — that are deployed in underground economies to facilitate click fraud, fake account registration, and other forms of online deception that undermine legitimate e-commerce and digital services. Xiong's most notable contribution, "Machine Learning Based CloudBot Detection Using Multi-Layer Traffic Statistics" (2019), demonstrates his innovative approach of applying machine learning techniques to network security challenges. By leveraging multi-layer traffic statistical analysis, his work provides practical detection methodologies for identifying malicious automated traffic — a particularly pressing concern as e-commerce and online transactions continue to expand globally. The paper has accumulated 11 citations, reflecting its relevance to the security research community. His research sits at the intersection of machine learning and network security, offering data-driven solutions to real-world cybersecurity threats. Students and researchers working on web security, traffic classification, or fraud detection will find Xiong's methodological approach — combining statistical traffic profiling with modern machine learning — both accessible and directly applicable to contemporary security challenges.
Research Focus
Key Achievements
Top Papers
- 1