面向智能调制识别的电磁信号灵巧诱骗方法

Mingliang Tao, Shuting Tang, Ling Wang

科研成果: 期刊稿件文章同行评审

摘要

Modulation classification techniques based deep learning are gradually being integrated and applied with their advantages in feature extraction and recognition performance. However,due to the vulnerability and limitation of the intelligent spectrum sensing model,the performance can be reduced by adding imperceptible perturbation to the original signal. Aiming at the vulnerability of intelligent electromagnetic signal modulation classification system,this paper carried out the research of electromagnetic signal deception method. Different from adding global disturbance on the signal,this method added disturbance to the specific sampling points,and the electromagnetic signal modulation classification system can be deceived smartly. The results show that this method could produce a relatively slight invisible disturbance,which deceives the system produce machine hallucinations and identify adversarial example as targeted signal and disturb the identification result of the system,so as to achieve the goal of“concealing the true and revealing the false”.

投稿的翻译标题Radio Signal Smart Deception Method for Intelligent Modulation Classification
源语言繁体中文
页(从-至)2496-2506
页数11
期刊Journal of Signal Processing
38
12
DOI
出版状态已出版 - 12月 2022

关键词

  • adversarial examples
  • deep learning
  • invisible deception
  • modulation classification

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