Malware Detection With Subspace Learning-Based One-Class Classification

Detecting malware is crucial for ensuring the security of computer systems. Traditional machine learning models face challenges in effectively detecting malware, mainly due to the class imbalance problem, where the number of malware samples is significantly smaller than that of non-malware samples....

詳細記述

書誌詳細

出版年:	IEEE Access
主要な著者:	Hasan H. Al-Khshali, Muhammad Ilyas, Fahad Sohrab, Moncef Gabbouj
フォーマット:	論文
言語:	英語
出版事項:	IEEE 2024-01-01
主題:	Machine learning malware one-class classification portable executable subspace support vector data description graph embedding
オンライン･アクセス:	https://ieeexplore.ieee.org/document/10549886/