Using Generative Adversarial Networks for Data Augmentation in Android Malware Detection-Reference-Cited by-同舟云学术

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Using Generative Adversarial Networks for Data Augmentation in Android Malware Detection

Published:2021-01-30 Issue: Volume: Page:
ISSN:
Container-title:2021 IEEE Conference on Dependable and Secure Computing (DSC)
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Author:

Chen Yi-Ming¹,Yang Chun-Hsien¹,Chen Guo-Chung¹

Affiliation:

1. National Central University,Dep. of Information Management,Taiwan

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9346211/9346228/09346277.pdf?arnumber=9346277

Cited by 16 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. KFFPDet: Android malicious application detection system with assisted detection of adversarial samples;Expert Systems with Applications;2024-10

2. GMADV: An android malware variant generation and classification adversarial training framework;Journal of Information Security and Applications;2024-08

3. SoK: Visualization-based Malware Detection Techniques;Proceedings of the 19th International Conference on Availability, Reliability and Security;2024-07-30

4. A novel machine learning approach for detecting first-time-appeared malware;Engineering Applications of Artificial Intelligence;2024-05

5. SynDroid: An adaptive enhanced Android malware classification method based on CTGAN-SVM;Computers & Security;2024-02

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