Enhanced Vulnerability Detection in SCADA Systems using Hyper-Parameter-Tuned Ensemble Learning-Reference-Cited by-同舟云学术

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Enhanced Vulnerability Detection in SCADA Systems using Hyper-Parameter-Tuned Ensemble Learning

Published:2021-10-20 Issue: Volume: Page:
ISSN:
Container-title:2021 International Conference on Information and Communication Technology Convergence (ICTC)
language:
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Author:

Ahakonye Love Allen Chijioke,Amaizu Gabriel Chukwunonso,Nwakanma Cosmas Ifeanyi,Lee Jae Min,Kim Dong-Seong

Funder

NRF

MEST

Grand Information Technology Research Center

IITP

MSIT

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9620727/9620211/09620215.pdf?arnumber=9620215

Cited by 5 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. Attack Target Detection Using Machine Learning on SCADA Gas Pipeline Data;2023 International Conference on Computational Science and Computational Intelligence (CSCI);2023-12-13

2. Optimal Tree Bayesian for the Characterization of Ciphered Network Communication Traffic;2023 International Conference on Artificial Intelligence in Information and Communication (ICAIIC);2023-02-20

3. Trees Bootstrap Aggregation for Detection and Characterization of IoT-SCADA Network Traffic;IEEE Transactions on Industrial Informatics;2023

4. Certain Investigations on Ensemble Learning and Machine Learning Techniques with IoT in Secured Cloud Service Provisioning;Proceedings of Data Analytics and Management;2023

5. A Novel Smart Contract Vulnerability Detection Method Based on Information Graph and Ensemble Learning;Sensors;2022-05-08

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