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Adversarial Attacks in Modulation Recognition With Convolutional Neural Networks

  • 【作者】Yun Lin,Haojun Zhao,Xuefei Ma,Ya Tu,Meiyu Wang
  • 【作者单位】1 College of Information and Communication Engineering, Harbin Engineering University, Harbin, China 2 Acoustic Science and Technology Laboratory, Harbin Engineering University, Harbin, China 3 College of Underwater Acoustic Engineering, Harbin Engineering University, Harbin, China 4 School of Information Science and Technology, Tibet University, Tibet, China
  • 【年份】2021
  • 【卷号】Vol.70 No.1
  • 【页码】389-401
  • 【ISSN】0018-9529;1558-1721
  • 【关键词】Modulation Perturbation methods Convolution Task analysis Feature extraction Training Security Adversarial examples convolutional neural network modulation recognition radio security white-box attacks 
  • 【摘要】 Deep learning models are vulnerable to adversarial attacks, by adding a subtle perturbation which is imperceptible to the human eye, a convolutional neural network can lead to erroneous results, which greatly reduces the reliability and security of...
  • 【文献类型】 期刊
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