Static malware classifiers learn packing artifacts and dataset composition biases rather than malicious semantics, as diagnosed by TRUSTEE interpretability across controlled dataset variations.
{TESSERACT}: Eliminating experimental bias in malware classifi- cation across space and time
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Beyond the Wrapper: Identifying Artifact Reliance in Static Malware Classifiers using TRUSTEE
Static malware classifiers learn packing artifacts and dataset composition biases rather than malicious semantics, as diagnosed by TRUSTEE interpretability across controlled dataset variations.