Meta-IDS: Meta-Learning-Based Smart Intrusion Detection System for Internet of Medical Things (IoMT) Network-Reference-Cited by-同舟云学术

Meta-IDS: Meta-Learning-Based Smart Intrusion Detection System for Internet of Medical Things (IoMT) Network

Published:2024-07-01 Issue:13 Volume:11 Page:23080-23095
ISSN:2327-4662
Container-title:IEEE Internet of Things Journal
language:
Short-container-title:IEEE Internet Things J.

Author:

Zukaib Umer¹^ORCID,Cui Xiaohui¹^ORCID,Zheng Chengliang¹,Hassan Mir²^ORCID,Shen Zhidong¹^ORCID

Affiliation:

1. Key Laboratory of Aerospace Information Security and Trusted Computing, Ministry of Education, School of Cyber Science and Engineering, Wuhan University, Wuhan, China

2. Department of Information Engineering and Computer Science, University of Trento, Trento, Italy

Funder

Key Research and Development Projects in Hubei Province

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/6488907/10570342/10496441.pdf?arnumber=10496441

Reference62 articles.

1. A comprehensive deep learning benchmark for IoT IDS

2. An explainable efficient flow-based Industrial IoT intrusion detection system

3. XMeDNN: An Explainable Deep Neural Network System for Intrusion Detection in Internet of Medical Things

4. IoT Intrusion Detection Using Machine Learning with a Novel High Performing Feature Selection Method

5. Intrusion Detection System to Advance Internet of Things Infrastructure-Based Deep Learning Algorithms

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Safeguarding the Internet of Health Things: advancements, challenges, and trust-based solution;Telecommunication Systems;2024-09-11

2. An RFE/Ridge-ML/DL based anomaly intrusion detection approach for securing IoMT system;Results in Engineering;2024-09