Feature Selection for Malware Detection Based on Reinforcement Learning

Feature Selection for Malware Detection Based on Reinforcement Learning

Machine learning based malware detection has been proved great success in the past few years. Most of the conventional methods are based on supervised learning, which relies on static features with labels. While selecting static features requires both human expertise and labor. New selections, which...

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Bibliographic Details
Main Authors: Zhiyang Fang, Junfeng Wang, Jiaxuan Geng, Xuan Kan
Format: Article
Language:English
Published: IEEE 2019-01-01
Series:IEEE Access
Subjects:
Feature selection
malware detection
deep reinforcement learning
Q-learning
Online Access:https://ieeexplore.ieee.org/document/8920059/

Internet

https://ieeexplore.ieee.org/document/8920059/

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