GOOSE Secure: A Comprehensive Dataset for In-Depth Analysis of GOOSE Spoofing Attacks in Digital Substations

Oscar A. Tobar-Rosero (), Omar A. Roa-Romero, Germán D. Rueda-Carvajal, Alexánder Leal-Piedrahita, Juan F. Botero-Vega, Sergio A. Gutierrez-Betancur, John W. Branch-Bedoya and Germán D. Zapata-Madrigal
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Oscar A. Tobar-Rosero: TyT Group, Universidad Nacional de Colombia, Medellín 050034, Colombia
Omar A. Roa-Romero: TyT Group, Universidad Nacional de Colombia, Medellín 050034, Colombia
Germán D. Rueda-Carvajal: TyT Group, Universidad Nacional de Colombia, Medellín 050034, Colombia
Alexánder Leal-Piedrahita: GITALab, Universidad de Antioquia, Medellín 050010, Colombia
Juan F. Botero-Vega: GITALab, Universidad de Antioquia, Medellín 050010, Colombia
Sergio A. Gutierrez-Betancur: GITALab, Universidad de Antioquia, Medellín 050010, Colombia
John W. Branch-Bedoya: TyT Group, Universidad Nacional de Colombia, Medellín 050034, Colombia
Germán D. Zapata-Madrigal: GIDIA Group, Universidad Nacional de Colombia, Medellín 050034, Colombia

Energies, 2024, vol. 17, issue 23, 1-19

Abstract: Cybersecurity in Critical Infrastructures, especially Digital Substations, has garnered significant attention from both the industrial and academic sectors. A commonly adopted approach to support research in this area involves the use of datasets, which consist of network traffic samples gathered during the operation of an infrastructure. However, creating such datasets from real-world electrical systems presents some challenges: (i) These datasets are often generated under controlled or idealized conditions, potentially overlooking the complexities of real-world operations within a digital substation; (ii) the captured data frequently contain sensitive information, making it difficult to share openly within the research community. This paper presents the creation of a new dataset aimed at advancing cybersecurity research, specifically focused on GOOSE spoofing attacks, given the crucial role of the GOOSE protocol in managing operational and control tasks within Digital Substations. The dataset highlights the real-world impacts of these attacks, demonstrating the execution of unintended operations under different operational scenarios, including both stable conditions and situations involving system failures. The data were collected from a laboratory testbed that replicates the actual functioning of a real digital substation with two bays. The experiments provided insights into key characteristics of GOOSE protocol traffic and the vulnerability of DS infrastructure to Spoofing Attacks.

Keywords: cybersecurity; dataset; digital substation; GOOSE protocol; IEC 61850; smart substation; spoofing attack (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2024
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