Data Augmentation with Generative Models for Improved Malware Detection: A Comparative Study-Reference-Cited by-同舟云学术

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Data Augmentation with Generative Models for Improved Malware Detection: A Comparative Study

Published:2019-10 Issue: Volume: Page:
ISSN:
Container-title:2019 IEEE 10th Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON)
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Author:

Burks Roland,Islam Kazi Aminul,Lu Yan,Li Jiang

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/8966519/8992916/08993085.pdf?arnumber=8993085

Cited by 29 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. Lightweight intrusion detection model based on CNN and knowledge distillation;Applied Soft Computing;2024-11

2. Synthetic Malware Using Deep Variational Autoencoders and Generative Adversarial Networks;EAI Endorsed Transactions on Internet of Things;2024-07-09

3. Multi-Level Generative Pretrained Transformer for Improving Malware Detection Performance;2024 7th International Conference on Artificial Intelligence and Big Data (ICAIBD);2024-05-24

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

5. DeepRSSI: Generative Model for Fingerprint-Based Localization;IEEE Access;2024

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