Studying the Robustness of Anti-Adversarial Federated Learning Models Detecting Cyberattacks in IoT Spectrum Sensors-Reference-Cited by-同舟云学术

Studying the Robustness of Anti-Adversarial Federated Learning Models Detecting Cyberattacks in IoT Spectrum Sensors

Published:2022 Issue: Volume: Page:1-12
ISSN:1545-5971
Container-title:IEEE Transactions on Dependable and Secure Computing
language:
Short-container-title:IEEE Trans. Dependable and Secure Comput.

Author:

Sanchez Sanchez Pedro Miguel¹^ORCID,Celdran Alberto Huertas²^ORCID,Schenk Timo²,Iten Adrian Lars Benjamin²,Bovet Gerome³,Perez Gregorio Martinez¹^ORCID,Stiller Burkhard²^ORCID

Affiliation:

1. Department of Information and Communications Engineering, University of Murcia, Murcia, Spain

2. Communication Systems Group (CSG) at the Department of Informatics (IfI), University of Zurich UZH, Zürich, Switzerland

3. Cyber-Defence Campus within armasuisse Science & Technology, Thun, Switzerland

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/8858/4358699/09878222.pdf?arnumber=9878222

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