Papers
1
Total Citations
36
H-Index
1
About
Dong Kun Lee is a distinguished researcher in the field of web security and network traffic analysis, best known for his pioneering empirical work on the classification of web robots. His seminal 2009 study, "Classification of web robots: An empirical study based on over one billion requests," has garnered 36 citations and remains a foundational reference for understanding automated web traffic. Lee’s major contribution lies in developing robust methodologies to distinguish between human users and malicious bots by analyzing vast datasets of HTTP requests, a critical advancement for cybersecurity and web analytics. His research has directly influenced the design of modern bot detection systems, helping organizations mitigate threats like data scraping and DDoS attacks. Beyond this landmark paper, Lee’s work continues to shape the intersection of machine learning and network security, earning him recognition as a key figure in the fight against web-based threats. For students and researchers, his studies offer a rigorous, data-driven approach to tackling real-world cybersecurity challenges.
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Top Papers
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