Are Machine Learning Models for Malware Detection Ready for Prime Time?

Lorenzo Cavallaro, Johannes Kinder*, Feargus Pendlebury, Fabio Pierazzi, Fabio Massacci, Eric Bodden, Antonino Sabetta

*Corresponding author for this work

Research output: Contribution to JournalArticleAcademicpeer-review

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Abstract

We investigate why the performance of machine learning models for malware detection observed in a lab setting often cannot be reproduced in practice. We discuss how to set up experiments mimicking a practical deployment and how to measure the robustness of a model over time.

Original languageEnglish
Pages (from-to)53-56
Number of pages4
JournalIEEE Security and Privacy
Volume21
Issue number2
Early online date14 Apr 2023
DOIs
Publication statusPublished - Apr 2023

Bibliographical note

Publisher Copyright:
© 2003-2012 IEEE.

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