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.
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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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