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...
محفوظ في:
المؤلفون الرئيسيون: | Yeong, Tyng Ling, Mohd Sani, Nor Fazlida, Abdullah, Mohd. Taufik, Abdul Hamid, Nor Asilah Wati |
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التنسيق: | مقال |
اللغة: | English |
منشور في: |
Elsevier Advanced Technology
2021
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الوصول للمادة أونلاين: | 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 |
الوسوم: |
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مواد مشابهة
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Nonnegative matrix factorization and metamorphic malware detection
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منشور في: (2019) -
Nonnegative matrix factorization and metamorphic malware
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منشور في: (2019) -
Metamorphic malware detection using structural features and nonnegative matrix factorization with hidden markov model
بواسطة: Ling, Yeong Tyng, وآخرون
منشور في: (2021) -
Metamorphic malware detection using structural features and nonnegative matrix factorization with hidden markov model
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منشور في: (2021) -
Short review on metamorphic malware detection in Hidden Markov Models
بواسطة: Yeong, T. Ling, وآخرون
منشور في: (2017)