Deep Learning Model with Sequential Features for Malware Classification

Deep Learning Model with Sequential Features for Malware Classification

Currently, malware shows an explosive growth trend. Demand for classifying malware is also increasing. The problem is the low accuracy of both malware detection and classification. From the static features of malicious families, a new deep learning method of TCN-BiGRU was proposed in this study, whi...

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Bibliographic Details
Main Authors: Xuan Wu, Yafei Song, Xiaoyi Hou, Zexuan Ma, Chen Chen
Format: Article
Language:English
Published: MDPI AG 2022-10-01
Series:Applied Sciences
Subjects:
deep learning
malware classification
sequential feature
temporal convolutional network
bidirectional gated recurrent unit
Online Access:https://www.mdpi.com/2076-3417/12/19/9994

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https://www.mdpi.com/2076-3417/12/19/9994

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