Intrusion Detection System for IoHT Devices using Federated Learning-Reference-Cited by-同舟云学术

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Intrusion Detection System for IoHT Devices using Federated Learning

Published:2023-05-20 Issue: Volume: Page:
ISSN:
Container-title:IEEE INFOCOM 2023 - IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS)
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Author:

Mosaiyebzadeh Fatemeh¹,Pouriyeh Seyedamin²,Parizi Reza M.³,Han Meng⁴,Batista Daniel Macêdo¹

Affiliation:

1. University of São Paulo,Department of Computer Science,Brazil

2. Kennesaw State University,Department of Information and Technology,Marietta,GA,USA

3. Kennesaw State University,Decentralized Science Lab,Marietta,GA,USA

4. Binjiang Institute of Zhejiang University,Hangzhou,Zhejiang,China

Funder

CNPq

Coor-denação de Aperfeiçoamento de Pessoal de Nível Superior - Brasil (CAPES)

FAPESP

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10225747/10225748/10225932.pdf?arnumber=10225932

Reference22 articles.

1. ECU-IoHT: A dataset for analyzing cyberattacks in Internet of Health Things

2. Intrusion Detection System for Healthcare Systems Using Medical and Network Data: A Comparison Study

3. Improved and Secured Electromyography in the Internet of Health Things;abbasi;IEEE Journal of Biomedical and Health Informatics,2021

4. Lightweight and Anonymity-Preserving User Authentication Scheme for IoT-Based Healthcare

5. Scikit-learn: Machine Learning in Python;pedregosa;The Journal of Machine Learning Research,2011

Cited by 4 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. Enhancing IoT Intrusion Detection with Federated Learning-Based CNN-GRU and LSTM-GRU Ensembles;2024 19th International Symposium on Wireless Communication Systems (ISWCS);2024-07-14

2. Meta-IDS: Meta-Learning-Based Smart Intrusion Detection System for Internet of Medical Things (IoMT) Network;IEEE Internet of Things Journal;2024-07-01

3. A Deep Learning-Based Framework for Strengthening Cybersecurity in Internet of Health Things (IoHT) Environments;Applied Sciences;2024-05-30

4. Federated Deep Learning Models for Intrusion Detection in IoT;Proceedings of the 7th International Conference on Networking, Intelligent Systems and Security;2024-04-18

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