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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Bibliografiset tiedot
Päätekijät: Yun Gao, Hirokazu Hasegawa, Yukiko Yamaguchi, Hajime Shimada
Aineistotyyppi: Artigo
Kieli:Inglês
Julkaistu: IEEE 2022-01-01
Sarja:IEEE Access
Aiheet:
Malware detection
machine learning
custom loss function
cost-sensitive learning
Linkit:https://ieeexplore.ieee.org/document/9766102/
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