Abstract:

In order to solve the problem of insufficient concealment of the generated electromagnetic signal adversarial examples, an electromagnetic signals no-targeted smoothing adversarial attack method based on Jacobian saliency maps (NTSA) is proposed, which balances the norms of the adversarial examples, generates a saliency map by calculating the Jacobian matrix according to the characteristics of the electromagnetic signal itself, and selects key feature points for smooth perturbation addition to generate adversarial examples. The experimental results on three network models trained using public datasets show that the NTSA can achieve a success rate of more than 90% on three network models. Compared with the same type of feature point method Jacobian-based saliency map attack (JSMA), the attack success rate of this method is improved by 30%, and the perturbation ratio can be reduced to less than 5%. The four concealment indexes, namely perturbation ratio, single-point perturbation distance, cosine similarity and Euclidean distance, show that the samples generated by the NTSA have the best concealment compared with the adversarial samples generated by other methods in this paper.

Key words: electromagnetic signal recognition, confrontation attacks, adversarial examples, smooth attacks, robustness