Comparative analysis on imbalanced multi-class classification for malware samples using CNN

Malware considered as one of the main actors in cyber attacks. Everyday, the number of unique malware samples are in the rise, however the ratio of benign software still greatly outnumbers malware samples. In machine learning, such datasets are known as imbalanced, where the majority class label gre...

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Bibliographic Details
Main Authors: Arwa Alzammam, Hamad Binsalleeh, Basil AsSdhan, Kostas Kyriakopoulos, Sangarapillai Lambotharan
Format: Default Conference proceeding
Published: 2020
Subjects:
Malware classification
Imbalanced dataset
Deep learning
Online Access:https://hdl.handle.net/2134/10007939.v1
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