Comparative Analysis of Feature Selection Methods with XGBoost for Malware Detection on the Drebin Dataset

Comparative Analysis of Feature Selection Methods with XGBoost for Malware Detection on the Drebin Dataset

Malware, or malicious software, continues to evolve alongside increasing cyberattacks targeting individual devices and critical infrastructure. Traditional detection methods, such as signature-based detection, are often ineffective against new or polymorphic malware. Therefore, advanced malware dete...

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Bibliographic Details
Main Authors: Ines Aulia Latifah, Fauzi Adi Rafrastara, Jevan Bintoro, Wildanil Ghozi, Waleed Mahgoub Osman
Format: Article
Language:English
Published: LPPM ISB Atma Luhur 2024-11-01
Series:Jurnal Sisfokom
Subjects:
android malware detection
drebin
information gain
xgboost
machine learning
Online Access:https://jurnal.atmaluhur.ac.id/index.php/sisfokom/article/view/2294
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