An electromagnetic signal adversarial sample detection method based on feature fusion

Aiming at the problem that the intelligent model of electromagnetic signal modulation recognition is vulnerable to adversarial samples, a feature fusion electromagnetic signal adversarial sample detection method is considered. At first, the electromagnetic signal samples after denoising are obtained through variational mode decomposition, and then the electromagnetic signal samples before and after denoising are sent into the neural network model, and then the cosine similarity value and confidence difference value of the model output vector before and after denoising are calculated. Finally, the two features are fused and sent into a neural network model for detection. Compared with the baseline method, this method has higher detection success rate in the experiment. This method has the advantages of low time complexity and easy implementation, and provides a novel adversarial sample detection method for the intelligent model of electromagnetic signal modulation recognition.