A Survey of Smart Grid Intrusion Detection Datasets

Mohammed M. Alani; Thar Baker

doi:10.3233/AISE230004

A Survey of Smart Grid Intrusion Detection Datasets

Mohammed M. Alani, Thar Baker

School of Arch, Tech and Eng

Research output: Chapter in Book/Conference proceeding with ISSN or ISBN › Conference contribution with ISSN or ISBN › peer-review

Abstract

Due to the rapid growth of smart grid applications all over the globe, it has become a more attractive target to malicious actors. Countries and stakeholders (e.g., governments) spend billions of dollars on ensuring the continuity and security of their smart grids for strategic and operational reasons. In fact, the risk associated with compromising a smart grid is considered among the highest in the cybersecurity world. This paper surveys a group of well-known smart grid intrusion detection datasets that are used in the development of machine learning-based intrusion detection systems. The study presents an analysis of these datasets and provides recommendations for researchers utilizing them.

Original language	English
Title of host publication	Workshop Proceedings of the 19th International Conference on Intelligent Environments
Pages	5-13
Number of pages	9
Volume	32
ISBN (Electronic)	9781643684055
DOIs	https://doi.org/10.3233/AISE230004
Publication status	Published - 27 Jun 2023

Publication series

Name	Workshop Proceedings of the 19th International Conference on Intelligent Environments (IE2023)
Publisher	IOS Press
ISSN (Print)	1875-4163

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10.3233/AISE230004Licence: CC BY-NC

Cite this

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title = "A Survey of Smart Grid Intrusion Detection Datasets",

abstract = "Due to the rapid growth of smart grid applications all over the globe, it has become a more attractive target to malicious actors. Countries and stakeholders (e.g., governments) spend billions of dollars on ensuring the continuity and security of their smart grids for strategic and operational reasons. In fact, the risk associated with compromising a smart grid is considered among the highest in the cybersecurity world. This paper surveys a group of well-known smart grid intrusion detection datasets that are used in the development of machine learning-based intrusion detection systems. The study presents an analysis of these datasets and provides recommendations for researchers utilizing them.",

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A Survey of Smart Grid Intrusion Detection Datasets. / Alani, Mohammed M.; Baker, Thar.
Workshop Proceedings of the 19th International Conference on Intelligent Environments. Vol. 32 2023. p. 5-13 (Workshop Proceedings of the 19th International Conference on Intelligent Environments (IE2023)).

Research output: Chapter in Book/Conference proceeding with ISSN or ISBN › Conference contribution with ISSN or ISBN › peer-review

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BT - Workshop Proceedings of the 19th International Conference on Intelligent Environments

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A Survey of Smart Grid Intrusion Detection Datasets

Abstract

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