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

Cavallaro, Lorenzo; Kinder, Johannes; Pendlebury, Feargus; Pierazzi, Fabio; (2023) Are Machine Learning Models for Malware Detection Ready for Prime Time? IEEE Security and Privacy Magazine , 21 (2) pp. 53-56. 10.1109/msec.2023.3236543. Green open access

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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.

Type: Article
Title: Are Machine Learning Models for Malware Detection Ready for Prime Time?
Open access status: An open access version is available from UCL Discovery
DOI: 10.1109/msec.2023.3236543
Publisher version: https://doi.org/10.1109/MSEC.2023.3236543
Language: English
Additional information: This version is the author accepted manuscript. For information on re-use, please refer to the publisher's terms and conditions.
UCL classification: UCL
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science
URI: https://discovery.ucl.ac.uk/id/eprint/10171046
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