Detecting Concept Drift in Evolving Malware Families Using Rule-Based Classifier Representations
arXiv:2604.22629v1 Announce Type: cross
Abstract: This work proposes a structural approach to concept drift detection in malware classification using decision tree rulesets. Classifiers are trained across temporal windows on the EMBER2024 dataset, and…