Sahil Garg
Trusted Explainable AI for 6G-Enabled Edge Cloud Ecosystem
Garg, Sahil; Kaur, Kuljeet; Aujla, Gagangeet Singh; Kaddoum, Georges; Garigipati, Prasad; Guizani, Mohsen
Authors
Kuljeet Kaur
Dr Gagangeet Aujla gagangeet.s.aujla@durham.ac.uk
Associate Professor in Computer Science
Georges Kaddoum
Prasad Garigipati
Mohsen Guizani
Abstract
The journey to the next decade of smart cellular connectivity, sixth-generation (6G) networks, has already begun, even though 6G is still in its nascent stages and far from its deployment. In telecommunications, 6G networks have gained the attention of the industry and academia. 6G is planned to succeed the 5G standard with almost 100 times greater speed. One of the exciting features of 6G is Edge Intelligence (EI), which is the coupling of Edge Computing with Artificial Intelligence (AI). So far, EI has yet to be a component of the existing and predecessor communication standards; thus, 6G will open up many opportunities with its deployment in the future. Nonetheless, integration of 6G with EI, in other words, Edge and AI, is also susceptible to various challenges, particularly security and privacy. Therefore, this article proposes a trusted AI-enabled intelligent architecture for the 6G-envisioned Edge Computing platform. The proposed architecture is based on the Explainable AI concept and is mainly used to ensure the security and privacy of the future 6G networks at the Edge. Following this, the work presents a detailed case study of employing the proposed framework. The preliminary discussion indicates some exciting findings and lays the foundation for future research. In a nutshell, the proposed architecture can be extended to different verticals, including, but not limited to, life-critical systems, like e-healthcare, autonomous vehicles, and traffic monitoring.
Citation
Garg, S., Kaur, K., Aujla, G. S., Kaddoum, G., Garigipati, P., & Guizani, M. (2023). Trusted Explainable AI for 6G-Enabled Edge Cloud Ecosystem. IEEE Wireless Communications, 30(3), 163-170. https://doi.org/10.1109/mwc.016.220047
Journal Article Type | Article |
---|---|
Acceptance Date | Mar 17, 2023 |
Publication Date | 2023-06 |
Deposit Date | Nov 2, 2023 |
Journal | IEEE Wireless Communications |
Print ISSN | 1536-1284 |
Electronic ISSN | 1558-0687 |
Publisher | Institute of Electrical and Electronics Engineers |
Peer Reviewed | Peer Reviewed |
Volume | 30 |
Issue | 3 |
Pages | 163-170 |
DOI | https://doi.org/10.1109/mwc.016.220047 |
Keywords | Electrical and Electronic Engineering; Computer Science Applications |
Public URL | https://durham-repository.worktribe.com/output/1875630 |
You might also like
Uncovering hidden and complex relations of pandemic dynamics using an AI driven system
(2024)
Journal Article
Downloadable Citations
About Durham Research Online (DRO)
Administrator e-mail: dro.admin@durham.ac.uk
This application uses the following open-source libraries:
SheetJS Community Edition
Apache License Version 2.0 (http://www.apache.org/licenses/)
PDF.js
Apache License Version 2.0 (http://www.apache.org/licenses/)
Font Awesome
SIL OFL 1.1 (http://scripts.sil.org/OFL)
MIT License (http://opensource.org/licenses/mit-license.html)
CC BY 3.0 ( http://creativecommons.org/licenses/by/3.0/)
Powered by Worktribe © 2024
Advanced Search