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...

Full beskrivning

Sparad:
Bibliografiska uppgifter
Huvudupphovsmän: Yun Gao, Hirokazu Hasegawa, Yukiko Yamaguchi, Hajime Shimada
Materialtyp: Artigo
Språk:Inglês
Publicerad: IEEE 2022-01-01
Serie:IEEE Access
Ämnen:
Malware detection
machine learning
custom loss function
cost-sensitive learning
Länkar:https://ieeexplore.ieee.org/document/9766102/
Taggar: Lägg till en tagg
Inga taggar, Lägg till första taggen!

Liknande verk