MLMD—A Malware-Detecting Antivirus Tool Based on the XGBoost Machine Learning Algorithm

This paper focuses on training machine learning models using the XGBoost and extremely randomized trees algorithms on two datasets obtained using static and dynamic analysis of real malicious and benign samples. We then compare their success rates—both mutually and with other algorithms, such as the...

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Bibliographic Details

Published in:	Applied sciences Vol. 12; no. 13; p. 6672
Main Authors:	Palša, Jakub, Ádám, Norbert, Hurtuk, Ján, Chovancová, Eva, Madoš, Branislav, Chovanec, Martin, Kocan, Stanislav
Format:	Journal Article
Language:	English
Published:	Basel MDPI AG 01.07.2022
Subjects:	Algorithms classification Contemporary problems cybersecurity dynamic analysis Machine learning Malware Software static analysis supervised machine learning
ISSN:	2076-3417, 2076-3417
Online Access:	Get full text
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