An Efficient Method for Generating Adversarial Malware Samples

An Efficient Method for Generating Adversarial Malware Samples

Deep learning methods have been applied to malware detection. However, deep learning algorithms are not safe, which can easily be fooled by adversarial samples. In this paper, we study how to generate malware adversarial samples using deep learning models. Gradient-based methods are usually used to...

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Bibliographic Details
Main Authors: Yuxin Ding, Miaomiao Shao, Cai Nie, Kunyang Fu
Format: Article
Language:English
Published: MDPI AG 2022-01-01
Series:Electronics
Subjects:
adversarial sample
malware detection
deep learning
convolutional neural network
Online Access:https://www.mdpi.com/2079-9292/11/1/154

Internet

https://www.mdpi.com/2079-9292/11/1/154

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