Kang-Ming Chang
Papers
1
Total Citations
2
H-Index
1
About
Kang-Ming Chang is a researcher whose work bridges cybersecurity, data mining, and internet governance. His research focuses on applying advanced computational techniques to analyze security threats and policy frameworks in digital ecosystems. In a notable study, Chang employed web crawling and association rule technology to mine the ICANN website for emerging security topics, demonstrating how automated data extraction can reveal patterns in internet governance announcements. This work, published in 2019, has garnered 2 citations, reflecting its niche but valuable contribution to understanding how policy and security intersect in domain name system management. Chang’s approach—combining practical web scraping with rule-based analysis—offers a replicable methodology for researchers tracking real-time security discourse. His contributions are particularly relevant for students and professionals interested in the automation of threat intelligence and the governance of critical internet infrastructure. By leveraging data-driven techniques, Chang provides a lens into the evolving landscape of cybersecurity, where policy announcements often precede technical vulnerabilities.
Research Focus
Key Achievements
Top Papers
- 1