The Library
Adversarial attacks on deep neural networks based modulation recognition
Tools
Tools
Tools
Liu, Mingqian, Zhang, Zhenju, Zhao, Nan and Chen, Yunfei (2022) Adversarial attacks on deep neural networks based modulation recognition. In: IEEE INFOCOM 2022 - IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS), New York, NY, USA, 02-05 May 2022 ISBN 9781665409261. doi:10.1109/infocomwkshps54753.2022.9798389
Research output not available from this repository.
Request-a-Copy directly from author or use local Library Get it For Me service.
Official URL: https://doi.org/10.1109/infocomwkshps54753.2022.97...
Abstract
Modulation recognition models based on deep neural network (DNN) have the advantages of automatic feature extraction, fast recognition and high accuracy. However, due to the interpretability defects, DNN models are vulnerable to adversarial examples designed by attackers. Most existing researches focus on the accuracy of modulation recognition models, while ignoring the huge threat of adversarial examples to the safety and reliability of the models. In the field of modulation recognition, many existing attack methods have good attack performance for simple neural networks, but poor performance for more complicated DNNs. Therefore, this paper proposes an adversarial attack method based on dynamic iterative. The proposed method uses a dynamic iterative step that changes with iteration instead of being fixed. Simulation results show that the proposed attack method has better attack performance when the disturbance is specified than the traditional attack methods.
| Item Type: | Conference Item (Paper) | ||||
|---|---|---|---|---|---|
| Divisions: | Faculty of Science, Engineering and Medicine > Engineering > Engineering | ||||
| SWORD Depositor: | Library Publications Router | ||||
| Publisher: | IEEE | ||||
| ISBN: | 9781665409261 | ||||
| Official Date: | 2 May 2022 | ||||
| Dates: |
|
||||
| DOI: | 10.1109/infocomwkshps54753.2022.9798389 | ||||
| Status: | Peer Reviewed | ||||
| Publication Status: | Published | ||||
| Access rights to Published version: | Restricted or Subscription Access | ||||
| Conference Paper Type: | Paper | ||||
| Title of Event: | IEEE INFOCOM 2022 - IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS) | ||||
| Type of Event: | Conference | ||||
| Location of Event: | New York, NY, USA | ||||
| Date(s) of Event: | 02-05 May 2022 |
Request changes or add full text files to a record
Repository staff actions (login required)
 |
View Item |
