mlsanityData to 14 Oct 2026

Adversarial Attacks on Deep-Learning Based Radio Signal Classification

arXiv 1808.07713 ↗First posted 23 Aug 2018cs.IT cs.CR cs.LGcited by 47

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Abstract (arXiv)

Deep learning (DL), despite its enormous success in many computer vision and language processing applications, is exceedingly vulnerable to adversarial attacks. We consider the use of DL for radio signal (modulation) classification tasks, and present practical methods for the crafting of white-box and universal black-box adversarial attacks in that application. We show that these attacks can considerably reduce the classification performance, with extremely small perturbations of the input. In particular, these attacks are significantly more powerful than classical jamming attacks, which raises significant security and robustness concerns in the use of DL-based algorithms for the wireless physical layer.

Key facts. Cited by 47 papers in the map (data through 14 Oct 2026). First posted on arXiv 23 Aug 2018.

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Citing papers per year: 2021: 12; 2022: 13; 2023: 5; 2024: 7; 2025: 8; 2026: 2.

47 papers.

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  1. 2021Adversarial Machine Learning for 5G Communications Securitycited by 12
  2. 2021Adversarial Attacks on Deep Learning Based Power Allocation in a Massive MIMO Networkcited by 11
  3. 2023ChatGPT is on the Horizon: Could a Large Language Model be Suitable for Intelligent Traffic Safety Research and Applications?cited by 9
  4. 2022Machine Learning in NextG Networks via Generative Adversarial Networkscited by 8
  5. 2021Adversarial Machine Learning for Flooding Attacks on 5G Radio Access Network Slicingcited by 6
  6. 2021Adversarial Attacks on Deep Learning Based mmWave Beam Prediction in 5G and Beyondcited by 6
  7. 2022Jamming Attacks on Federated Learning in Wireless Networkscited by 6
  8. 2021Membership Inference Attack and Defense for Wireless Signal Classifiers with Deep Learningcited by 5
  9. 2022Wild Networks: Exposure of 5G Network Infrastructures to Adversarial Examplescited by 5
  10. 2024Countermeasures Against Adversarial Examples in Radio Signal Classificationcited by 5
  11. 2021Adversarial Attacks against Deep Learning Based Power Control in Wireless Communicationscited by 4
  12. 2021Universal Adversarial Attacks on Neural Networks for Power Allocation in a Massive MIMO Systemcited by 3
35 more
  1. 2021Binarized ResNet: Enabling Robust Automatic Modulation Classification at the resource-constrained Edgecited by 3
  2. 2022Mixture GAN For Modulation Classification Resiliency Against Adversarial Attackscited by 3
  3. 2022Secure and Trustworthy Artificial Intelligence-Extended Reality (AI-XR) for Metaversescited by 3
  4. 2024A Hybrid Training-time and Run-time Defense Against Adversarial Attacks in Modulation Classificationcited by 3
  5. 2021On the benefits of robust models in modulation recognitioncited by 2
  6. 2021SafeAMC: Adversarial training for robust modulation recognition modelscited by 2
  7. 2023Radio Signal Classification by Adversarially Robust Quantum Machine Learningcited by 2
  8. 2025Adaptive Meta-learning-based Adversarial Training for Robust Automatic Modulation Classificationcited by 2
  9. 2025Attention-based Adversarial Robust Distillation in Radio Signal Classifications for Low-Power IoT Devicescited by 2
  10. 2025Vision Transformer with Adversarial Indicator Token against Adversarial Attacks in Radio Signal Classificationscited by 2
  11. 2025Adapt under Attack and Domain Shift: Unified Adversarial Meta-Learning and Domain Adaptation for Robust Automatic Modulation Classificationcited by 2
  12. 2022Real-time Over-the-air Adversarial Perturbations for Digital Communications using Deep Neural Networkscited by 1
  13. 2022Downlink Power Allocation in Massive MIMO via Deep Learning: Adversarial Attacks and Trainingcited by 1
  14. 2022Universal Fourier Attack for Time Seriescited by 1
  15. 2022Adversarial Machine Learning and Defense Game for NextG Signal Classification with Deep Learningcited by 1
  16. 2023AIR: Threats of Adversarial Attacks on Deep Learning-Based Information Recoverycited by 1
  17. 2023Magmaw: Modality-Agnostic Adversarial Attacks on Machine Learning-Based Wireless Communication Systemscited by 1
  18. 2023Adversarial Attacks on LoRa Device Identification and Rogue Signal Detection with Deep Learningcited by 1
  19. 2024Adversarial Attack and Defense for LoRa Device Identification and Authentication via Deep Learningcited by 1
  20. 2021A Robust Adversarial Network-Based End-to-End Communications System With Strong Generalization Ability Against Adversarial Attackscited by 0
  21. 2021Covert Communications via Adversarial Machine Learning and Reconfigurable Intelligent Surfacescited by 0
  22. 2022Low-Interception Waveform: To Prevent the Recognition of Spectrum Waveform Modulation via Adversarial Examplescited by 0
  23. 2022A Review of the Convergence of 5G/6G Architecture and Deep Learningcited by 0
  24. 2022Deep Multi-Scale Representation Learning with Attention for Automatic Modulation Classificationcited by 0
  25. 2022Maximum Likelihood Distillation for Robust Modulation Classificationcited by 0
  26. 2024Optimal Zero-Shot Detector for Multi-Armed Attackscited by 0
  27. 2024Adversarial Robustness of Distilled and Pruned Deep Learning-based Wireless Classifierscited by 0
  28. 2024Golden Ratio Search: A Low-Power Adversarial Attack for Deep Learning based Modulation Classificationcited by 0
  29. 2024Signal Adversarial Examples Generation for Signal Detection Network via White-Box Attackcited by 0
  30. 2025A look at adversarial attacks on radio waveforms from discrete latent spacecited by 0
  31. 2025A Neural Rejection System Against Universal Adversarial Perturbations in Radio Signal Classificationcited by 0
  32. 2025ZK-SenseLM: Verifiable Large-Model Wireless Sensing with Selective Abstention and Zero-Knowledge Attestationcited by 0
  33. 2025Real-World Adversarial Attacks on RF-Based Drone Detectorscited by 0
  34. 2026CITADEL: CSI-Based Jamming Detection and Open-Set Classification for IIoT Networkscited by 0
  35. 2026QUASAR: A Quantum-Classical Neural Network for SAR Satellite Physical-Layer Authenticationcited by 0