N-gram MalGAN: Evading machine learning detection via feature n-gram

N-gram MalGAN: Evading machine learning detection via feature n-gram

In recent years, many adversarial malware examples with different feature strategies, especially GAN and its variants, have been introduced to handle the security threats, e.g., evading the detection of machine learning detectors. However, these solutions still suffer from problems of complicated de...

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Bibliographic Details
Main Authors: Enmin Zhu, Jianjie Zhang, Jijie Yan, Kongyang Chen, Chongzhi Gao
Format: Article
Language:English
Published: KeAi Communications Co., Ltd. 2022-08-01
Series:Digital Communications and Networks
Subjects:
Machine learning
N-gram
MalGAN
Adversarial examples
Online Access:http://www.sciencedirect.com/science/article/pii/S2352864821000973

Internet

http://www.sciencedirect.com/science/article/pii/S2352864821000973

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