PlausMal-GAN: Plausible Malware Training Based on Generative Adversarial Networks for Analogous Zero-Day Malware Detection-Reference-Cited by-同舟云学术

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PlausMal-GAN: Plausible Malware Training Based on Generative Adversarial Networks for Analogous Zero-Day Malware Detection

Published:2023-01-01 Issue:1 Volume:11 Page:82-94
ISSN:2168-6750
Container-title:IEEE Transactions on Emerging Topics in Computing
language:
Short-container-title:IEEE Trans. Emerg. Topics Comput.

Author:

Won Dong-Ok¹^ORCID,Jang Yong-Nam²^ORCID,Lee Seong-Whan³^ORCID

Affiliation:

1. Department of Artificial Intelligence Convergence, Hallym University, Chuncheon, South Korea

2. Department of Brain and Cognitive Engineering, Korea University, Seoul, South Korea

3. Department of Artificial Intelligence, Korea University, Seoul, South Korea

Funder

Ministry of Science and ICT South Korea

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computer Science Applications,Human-Computer Interaction,Information Systems,Computer Science (miscellaneous)

Link

http://xplorestaging.ieee.org/ielx7/6245516/10058698/09767588.pdf?arnumber=9767588

Reference52 articles.

1. Zero-day malware detection using transferred generative adversarial networks based on deep autoencoders

2. Detection of Malicious Code Variants Based on Deep Learning

3. Malware Detection Based on Deep Learning of Behavior Graphs

4. Use of Data Visualisation for Zero-Day Malware Detection

5. Unmasking Clever Hans predictors and assessing what machines really learn

Cited by 20 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. A review of deep learning based malware detection techniques;Neurocomputing;2024-09

2. Generative Adversarial Networks in Anomaly Detection and Malware Detection: A Comprehensive Survey;Advances in Artificial Intelligence Research;2024-08-30

3. Efficient malware detection using hybrid approach of transfer learning and generative adversarial examples with image representation;Expert Systems;2024-08-13

4. Zero-Ran Sniff: A zero-day ransomware early detection method based on zero-shot learning;Computers & Security;2024-07

5. Deep Convolutional Generative Adversarial Networks in Image-Based Android Malware Detection;Computers;2024-06-19

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