A Novel Attack Detection Scheme for the Industrial Internet of Things Using a Lightweight Random Neural Network-Reference-Cited by-同舟云学术

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A Novel Attack Detection Scheme for the Industrial Internet of Things Using a Lightweight Random Neural Network

Published:2020 Issue: Volume:8 Page:89337-89350
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Latif Shahid^ORCID,Zou Zhuo^ORCID,Idrees Zeba^ORCID,Ahmad Jawad^ORCID

Funder

NSFC

Shanghai Municipal Science and Technology Major Project

ZJ Lab

Shanghai Platform for Neuromorphic and AI Chip

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science

Link

http://xplorestaging.ieee.org/ielx7/6287639/8948470/09091574.pdf?arnumber=9091574

Cited by 120 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. Recent endeavors in machine learning-powered intrusion detection systems for the Internet of Things;Journal of Network and Computer Applications;2024-09

3. Securing IIoT operations with recurrent federated network-based enhanced local search grasshopper;Neural Computing and Applications;2024-08-06

4. A lightweight optimized intrusion detection system using machine learning for edge-based IIoT security;Telecommunication Systems;2024-07-26

5. BFLIDS: Blockchain-Driven Federated Learning for Intrusion Detection in IoMT Networks;Sensors;2024-07-15

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