Evading Anti-Malware Engines With Deep Reinforcement Learning

Evading Anti-Malware Engines With Deep Reinforcement Learning

To reduce the risks of malicious software, malware detection methods using machine learning have received tremendous attention in recent years. Most of the conventional methods are based on supervised learning, which relies on static features with definite labels. However, recent studies have shown...

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Bibliographic Details
Main Authors: Zhiyang Fang, Junfeng Wang, Boya Li, Siqi Wu, Yingjie Zhou, Haiying Huang
Format: Article
Language:English
Published: IEEE 2019-01-01
Series:IEEE Access
Subjects:
Anti-malware engines evasion
deep machine learning
malware detection
reinforcement learning
Online Access:https://ieeexplore.ieee.org/document/8676031/

Internet

https://ieeexplore.ieee.org/document/8676031/

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