Show/Hide Menu
Hide/Show Apps
Logout
Türkçe
Türkçe
Search
Search
Login
Login
OpenMETU
OpenMETU
About
About
Open Science Policy
Open Science Policy
Open Access Guideline
Open Access Guideline
Postgraduate Thesis Guideline
Postgraduate Thesis Guideline
Communities & Collections
Communities & Collections
Help
Help
Frequently Asked Questions
Frequently Asked Questions
Guides
Guides
Thesis submission
Thesis submission
MS without thesis term project submission
MS without thesis term project submission
Publication submission with DOI
Publication submission with DOI
Publication submission
Publication submission
Supporting Information
Supporting Information
General Information
General Information
Copyright, Embargo and License
Copyright, Embargo and License
Contact us
Contact us
GEMLIDS-MIOT: A Green Effective Machine Learning Intrusion Detection System based on Federated Learning for Medical IoT network security hardening
Date
2024-03-01
Author
Ioannou, Iacovos
Nagaradjane, Prabagarane
Angın, Pelin
Balasubramanian, Palaniappan
Kavitha, Karthick Jeyagopal
Murugan, Palani
Vassiliou, Vasos
Metadata
Show full item record
This work is licensed under a
Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License
.
Item Usage Stats
93
views
0
downloads
Cite This
URI
https://hdl.handle.net/11511/108965
Journal
COMPUTER COMMUNICATIONS
Collections
Department of Computer Engineering, Article
Citation Formats
IEEE
ACM
APA
CHICAGO
MLA
BibTeX
I. Ioannou et al., “GEMLIDS-MIOT: A Green Effective Machine Learning Intrusion Detection System based on Federated Learning for Medical IoT network security hardening,”
COMPUTER COMMUNICATIONS
, vol. 218, pp. 209–239, 2024, Accessed: 00, 2024. [Online]. Available: https://hdl.handle.net/11511/108965.
