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Metamorphic malware detection using structural features and nonnegative matrix factorization with hidden markov model

Metamorphic malware modifies its code structure using a morphing engine to evade traditional signature-based detection. Previous research has shown the use of opcode instructions as feature representation with Hidden Markov Model in the context of metamorphic malware detection. However, it would be...

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書誌詳細
主要な著者:	Ling, Yeong Tyng, Mohd Sani, Nor Fazlida, Abdullah, Mohd Taufik, Abdul Hamid, Nor Asilah Wati
フォーマット:	論文
出版事項:	Springer Cham 2021
オンライン･アクセス:	http://psasir.upm.edu.my/id/eprint/94169/ https://link.springer.com/article/10.1007/s11416-021-00404-z
タグ:	タグ追加タグなし, このレコードへの初めてのタグを付けませんか!

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