Annotation
Concept learning is a relevant explainable AI method which has already been applied to malware characterization, e.g. on the EMBER dataset. This work will focus on the larger SOREL-20M dataset. The main aim is to compare the obtained characterizations, detected noise level, etc., and cross-validate the overall applicability of the methodology.