Detection of Exceptional Malware Variants Using Deep Boosted Feature Spaces and Machine Learning

Detection of Exceptional Malware Variants Using Deep Boosted Feature Spaces and Machine Learning

Malware is a key component of cyber-crime, and its analysis is the first line of defence against cyber-attack. This study proposes two new malware classification frameworks: Deep Feature Space-based Malware classification (DFS-MC) and Deep Boosted Feature Space-based Malware classification (DBFS-MC)...

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Bibliographic Details
Main Authors:	Muhammad Asam, Shaik Javeed Hussain, Mohammed Mohatram, Saddam Hussain Khan, Tauseef Jamal, Amad Zafar, Asifullah Khan, Muhammad Umair Ali, Umme Zahoora
Format:	Article
Language:	English
Published:	MDPI AG 2021-11-01
Series:	Applied Sciences
Subjects:	malware classification detection deep learning deep features convolutional neural networks transfer learning
Online Access:	https://www.mdpi.com/2076-3417/11/21/10464

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