HFAD: Homomorphic Filtering Adversarial Defense Against Adversarial Attacks in Automatic Modulation Classification-Reference-Cited by-同舟云学术

HFAD: Homomorphic Filtering Adversarial Defense Against Adversarial Attacks in Automatic Modulation Classification

Published:2024-06 Issue:3 Volume:10 Page:880-892
ISSN:2332-7731
Container-title:IEEE Transactions on Cognitive Communications and Networking
language:
Short-container-title:IEEE Trans. Cogn. Commun. Netw.

Author:

Zhang Sicheng¹^ORCID,Lin Yun¹^ORCID,Yu Jiarun¹^ORCID,Zhang Jianting²,Xuan Qi³^ORCID,Xu Dongwei³^ORCID,Wang Juzhen⁴^ORCID,Wang Meiyu⁵

Affiliation:

1. College of Information and Communication Engineering, Harbin Engineering University, Harbin, China

2. China People’s Liberation Army General Equipment Department, No. 91977 Unit of People’s Liberation Army of China, Beijing, China

3. Institute of Cyberspace Security, Zhejiang University of Technology, Hangzhou, China

4. School of Electronic Information, Wuhan University, Wuhan, China

5. College of Communication Engineering, Hangzhou Dianzi University, Hangzhou, China

Funder

National Natural Science Foundation of China

National Key Research and Development Program of China

Key Laboratory of Advanced Marine Communication and Information Technology, Ministry of Industry and Information Technology, Harbin Engineering University, Harbin, China

Key R&D Program of Zhejiang

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/6687307/10551670/10418157.pdf?arnumber=10418157

Reference44 articles.

1. Over-the-Air Deep Learning Based Radio Signal Classification

2. A Survey of Modulation Classification Using Deep Learning: Signal Representation and Data Preprocessing

3. GLR-SEI: Green and Low Resource Specific Emitter Identification Based on Complex Networks and Fisher Pruning

4. LT-SEI: Long-Tailed Specific Emitter Identification Based on Decoupled Representation Learning in Low-Resource Scenarios

5. Few-Shot Specific Emitter Identification Using Asymmetric Masked Auto-Encoder