Effective Industrial Internet of Things Vulnerability Detection Using Machine Learning-Reference-Cited by-同舟云学术

Effective Industrial Internet of Things Vulnerability Detection Using Machine Learning

Published:2022-11-01 Issue: Volume: Page:
ISSN:
Container-title:2022 5th Information Technology for Education and Development (ITED)
language:
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Author:

Nwakanma Cosmas Ifeanyi¹,Ahakonye Love Allen Chijioke²,Njoku Judith Nkechinyere²,Eze Joy³,Kim Dong-Seong²

Affiliation:

1. ICT Convergence Research Center, Kumoh National Institute of Technology,Korea

2. Kumoh National Institute of Technology,IT-Convergence Engineering,Korea

3. Goldsmiths, University of London,United Kingdom

Funder

NRF

MEST

IITP

MSIT

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10051167/10051171/10051622.pdf?arnumber=10051622

Reference23 articles.

1. Increasing the Trustworthiness in the Industrial IoT Networks Through a Reliable Cyberattack Detection Model

2. Towards an efficient anomaly‐based intrusion detection for software‐defined networks

3. De-tection of DoH Tunnels using Time-Series Classification of Encrypted Traffic;montazerishatoori;2020 IEEE Intl Conf on Dependable Autonomic and Secure Computing Intl Conf on Pervasive Intelligence and Computing Intl Conf on Cloud and Big Data Computing Intl Conf on Cyber Science and Technology Congress (DASC/PiCom/CBDCom/CyberSciTech),2020

4. Efficient Classification of Enciphered SCADA Network Traffic in Smart Factory Using Decision Tree Algorithm

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3. Detection of Man-in-the-Middle (MitM) Cyber-Attacks in Oil and Gas Process Control Networks Using Machine Learning Algorithms;Future Internet;2023-08-21