Paper Accepted at IEEE FMLDS 2026

A paper by Chaeri Jung and Chaeyoung Lee, “Cleansing Label Contamination in Popularity-based Ranking Lists for Robust DGA Detection”, has been accepted as a full paper at the IEEE International Conference on Future Machine Learning and Data Science (FMLDS) 2026, to be held in Kobe, Japan in November 2026. The work shows that popularity-based ranking lists commonly used as benign data contain morphologically anomalous domains, and proposes a log-likelihood-ratio cleansing method that improves DGA detection performance.