Threats of Adversarial Attacks in DNN-Based Modulation Recognition-Reference-Cited by-同舟云学术

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Threats of Adversarial Attacks in DNN-Based Modulation Recognition

Published:2020-07 Issue: Volume: Page:
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Container-title:IEEE INFOCOM 2020 - IEEE Conference on Computer Communications
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Author:

Lin Yun,Zhao Haojun,Tu Ya,Mao Shiwen,Dou Zheng

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9146503/9155217/09155389.pdf?arnumber=9155389

Cited by 81 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. AIR: Threats of Adversarial Attacks on Deep Learning-Based Information Recovery;IEEE Transactions on Wireless Communications;2024-09

2. Novel framework for learning performance prediction using pattern identification and deep learning;Data Technologies and Applications;2024-08-21

3. Channel-Robust Class-Universal Spectrum-Focused Frequency Adversarial Attacks on Modulated Classification Models;IEEE Transactions on Cognitive Communications and Networking;2024-08

4. RobustRMC: Robustness Interpretable Deep Neural Network for Radio Modulation Classification;IEEE Transactions on Cognitive Communications and Networking;2024-08

5. Adversarial Attacks and Defenses for Wireless Signal Classifiers Using CDI-aware GANs;ICC 2024 - IEEE International Conference on Communications;2024-06-09

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