Edge Learning for 6G-Enabled Internet of Things: A Comprehensive Survey of Vulnerabilities, Datasets, and Defenses-Reference-Cited by-同舟云学术

Edge Learning for 6G-Enabled Internet of Things: A Comprehensive Survey of Vulnerabilities, Datasets, and Defenses

Published:2023 Issue:4 Volume:25 Page:2654-2713
ISSN:1553-877X
Container-title:IEEE Communications Surveys & Tutorials
language:
Short-container-title:IEEE Commun. Surv. Tutorials

Author:

Ferrag Mohamed Amine¹^ORCID,Friha Othmane²^ORCID,Kantarci Burak³^ORCID,Tihanyi Norbert¹^ORCID,Cordeiro Lucas⁴^ORCID,Debbah Merouane⁵^ORCID,Hamouda Djallel⁶^ORCID,Al-Hawawreh Muna⁷^ORCID,Choo Kim-Kwang Raymond⁸^ORCID

Affiliation:

1. AI and Digital Science Research Center, Technology Innovation Institute, Abu Dhabi, UAE

2. Networks and Systems Laboratory, Badji Mokhtar-Annaba University, Annaba, Algeria

3. School of Electrical Engineering and Computer Science, University of Ottawa, Ottawa, Canada

4. Department of Computer Science, The University of Manchester, Manchester, U.K

5. Khalifa University 6G Research Center, Khalifa University of Science and Technology, Abu Dhabi, UAE

6. Department of Computer Science, Labstic Laboratory, Guelma University, Guelma, Algeria

7. School of Information Technology, Deakin University, Burwood, VIC, Australia

8. Department of Information Systems and Cyber Security, University of Texas at San Antonio, San Antonio, TX, USA

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/9739/10324457/10255264.pdf?arnumber=10255264

Reference300 articles.

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4. The Roadmap to 6G: AI Empowered Wireless Networks

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