Malware Detection Using LightGBM With a Custom Logistic Loss Function

The increased spread of malicious software (malware) through the internet remains a serious threat. Malware authors use obfuscation and deformation techniques to generate new types than can evade traditional detection methods. Hence, it is widely expected that machine learning methods can classify m...

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Библиографические подробности
Главные авторы: Yun Gao, Hirokazu Hasegawa, Yukiko Yamaguchi, Hajime Shimada
Формат: Artigo
Язык:Inglês
Опубликовано: IEEE 2022-01-01
Серии:IEEE Access
Предметы:
Malware detection
machine learning
custom loss function
cost-sensitive learning
Online-ссылка:https://ieeexplore.ieee.org/document/9766102/
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