Pilsung Kang
Seoul National University · Computer Science
About the Lab
Professor Pilsung Kang's research lab specializes in cybersecurity, with a focus on insider threat detection, user behavior analytics, and anomaly detection in enterprise systems. The lab develops advanced behavioral modeling and machine learning techniques to identify malicious activities by authorized users that traditional rule-based systems often miss. Their work emphasizes real-world applicability through analysis of user log data and adaptive detection algorithms. The lab also explores privacy-preserving methods to balance security and user confidentiality.
Research Overview
Research Output Trend
Figures are computed from collected data and may differ slightly.
Selected Papers
15Insider threats are malicious activities by authorized users, such as theft of intellectual property or security information, fraud, and sabotage. Although the number of insider threats is much lower than external network attacks, insider threats can cause extensive damage. As insiders are very familiar with an organization’s system, it is very difficult to detect their malicious behavior. Traditional insider-threat detection methods focus on rule-based approaches built by domain experts, but th
Research Areas
Dive deeper into Pilsung Kang's research on Nubint
Open this lab's papers in the app to read with AI, summarize, and cite in your writing.