Elsevier
Computers in Biology and Medicine
,  volume 186 ,  pages 109603

Feature efficiency in IoMT security: A comprehensive framework for threat detection with DNN and ML

Publication type: Journal Article
Publication date: 2025-03-01
Elsevier
scimago Q1
wos Q1
SJR: 1.447
CiteScore: 13.0
Impact factor: 6.3
ISSN: 00104825, 18790534
Abstract
Background:To address critical security challenges in the Internet of Medical Things (IoMT), this study develops a feature selection framework to improve detection accuracy and computational efficiency in IoMT cybersecurity. By optimizing feature selection, the framework aims to enhance the security and operational integrity of real-time healthcare systems.
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Pinar M., Aktas A., Ulku E. E. Feature efficiency in IoMT security: A comprehensive framework for threat detection with DNN and ML // Computers in Biology and Medicine. 2025. Vol. 186. p. 109603.
GOST all authors (up to 50) Copy
Pinar M., Aktas A., Ulku E. E. Feature efficiency in IoMT security: A comprehensive framework for threat detection with DNN and ML // Computers in Biology and Medicine. 2025. Vol. 186. p. 109603.
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RIS Copy
TY - JOUR
DO - 10.1016/j.compbiomed.2024.109603
UR - https://linkinghub.elsevier.com/retrieve/pii/S0010482524016883
TI - Feature efficiency in IoMT security: A comprehensive framework for threat detection with DNN and ML
T2 - Computers in Biology and Medicine
AU - Pinar, Merve
AU - Aktas, Abdulsamet
AU - Ulku, Eyup Emre
PY - 2025
DA - 2025/03/01
PB - Elsevier
SP - 109603
VL - 186
PMID - 39746295
SN - 0010-4825
SN - 1879-0534
ER -
BibTex
Cite this
BibTex (up to 50 authors) Copy
@article{2025_Pinar,
author = {Merve Pinar and Abdulsamet Aktas and Eyup Emre Ulku},
title = {Feature efficiency in IoMT security: A comprehensive framework for threat detection with DNN and ML},
journal = {Computers in Biology and Medicine},
year = {2025},
volume = {186},
publisher = {Elsevier},
month = {mar},
url = {https://linkinghub.elsevier.com/retrieve/pii/S0010482524016883},
pages = {109603},
doi = {10.1016/j.compbiomed.2024.109603}
}