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Structural features with nonnegative matrix factorization for metamorphic malware detection

Metamorphic malware is well known for evading signature-based detection by exploiting various code obfuscation techniques. Current metamorphic malware detection approaches require some prior knowledge during feature engineering stage to extract patterns and behaviors from malware. In this paper, we...

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書誌詳細
主要な著者:	Yeong, Tyng Ling, Mohd Sani, Nor Fazlida, Abdullah, Mohd. Taufik, Abdul Hamid, Nor Asilah Wati
フォーマット:	論文
言語:	English
出版事項:	Elsevier Advanced Technology 2021
オンライン･アクセス:	http://psasir.upm.edu.my/id/eprint/95181/1/Structural%20features%20with%20nonnegative%20matrix%20factorization%20for%20metamorphic%20malware%20detection.pdf http://psasir.upm.edu.my/id/eprint/95181/ https://www.sciencedirect.com/science/article/pii/S0167404821000407
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