A comprehensive dataset from a smart grid testbed for machine learning based CPS security research
Ahmed, Chuadhry Mujeeb and Kandasamy, Nandha Kumar; Abie, Habtamu and Ranise, Silvio and Verderame, Luca and Cambiaso, Enrico and Ugarelli, Rita and Giunta, Gabriele and Praça, Isabel and Battisti, Federica, eds. (2021) A comprehensive dataset from a smart grid testbed for machine learning based CPS security research. In: Cyber-Physical Security for Critical Infrastructures Protection - 1st International Workshop, CPS4CIP 2020, Revised Selected Papers. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 12618 . Springer, GBR, pp. 123-135. ISBN 9783030697815 (https://doi.org/10.1007/978-3-030-69781-5_9)
Preview |
Text.
Filename: Ahmed_Kandasamy_CPSCIP_2020_A_comprehensive_dataset_from_a_smart_grid_testbed_for_machine_learning.pdf
Accepted Author Manuscript Download (1MB)| Preview |
Abstract
Data-sets play a crucial role in advancing the research. However, getting access to real-world data becomes difficult when it comes to critical infrastructures and more so if that data is being acquired for security research. In this work, a comprehensive dataset from a real-world smart electric grid testbed is collected and shared with the research community. A few of the unique features of the dataset and testbed are highlighted.
ORCID iDs
Ahmed, Chuadhry Mujeeb ORCID: https://orcid.org/0000-0003-3644-0465 and Kandasamy, Nandha Kumar; Abie, Habtamu, Ranise, Silvio, Verderame, Luca, Cambiaso, Enrico, Ugarelli, Rita, Giunta, Gabriele, Praça, Isabel and Battisti, Federica-
-
Item type: Book Section ID code: 77723 Dates: DateEvent18 February 2021Published18 September 2020Published Online7 August 2020AcceptedSubjects: Science > Mathematics > Electronic computers. Computer science Department: Faculty of Science > Computer and Information Sciences Depositing user: Pure Administrator Date deposited: 09 Sep 2021 01:37 Last modified: 25 Dec 2024 01:07 URI: https://strathprints.strath.ac.uk/id/eprint/77723