Towards Feature Selection for Detecting LDDoS in SD-IoT of Smart Grids: A Multi-correlation Information EA-based Method-Reference-Cited by-同舟云学术

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Towards Feature Selection for Detecting LDDoS in SD-IoT of Smart Grids: A Multi-correlation Information EA-based Method

Published:2023-10-13 Issue: Volume: Page:60-66
ISSN:
Container-title:Proceedings of the 2023 2nd International Symposium on Computing and Artificial Intelligence
language:
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Author:

Huan Xuanyu¹^ORCID,Zhao Jianpeng²^ORCID,Chen Guolin³^ORCID,Li Xianchao³^ORCID,Cui Yunhe¹^ORCID,Yang Hongzhen²^ORCID

Affiliation:

1. Guizhou Xiangming technology co., ltd. Guiyang, China; state key laboratory of big data, college of computer science and technology, Guizhou University, China

2. State grid Zhejiang electric power Co.,ltd., information and telecommunication branch, China

3. Guizhou Xiangming technology co., ltd, China

Funder

Science and Technology Project of State Grid Zhejiang Electric Power Co., Ltd.

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3640771.3640786

Reference16 articles.

1. Towards DDoS detection mechanisms in Software-Defined Networking

2. Performance and Features: Mitigating the Low-Rate TCP-Targeted DoS Attack via SDN

3. Augmented whale feature selection for IoT attacks: Structure, analysis and applications

4. Multi‐objective‐based feature selection for DDoS attack detection in IoT networks

5. A Multikernel and Metaheuristic Feature Selection Approach for IoT Malware Threat Hunting in the Edge Layer

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