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Extended Abstract: Assessing GNSS Vulnerabilities in Smart Grids

Canbolat, Sine ORCID iD icon 1; Fruböse, Clemens 2; Elbez, Ghada ORCID iD icon 1; Hagenmeyer, Veit ORCID iD icon 1
1 Institut für Automation und angewandte Informatik (IAI), Karlsruher Institut für Technologie (KIT)
2 Institut für Informationssicherheit und Verlässlichkeit (KASTEL), Karlsruher Institut für Technologie (KIT)

Abstract (englisch):

For the future power grid, the need for time-synchronized measurement data of high resolution also comes with the drawback of an increasing reliance on Global Navigation Satellite Signals (GNSSs) for time synchronization. Although the manipulation of GNSS signals has been extensively investigated, the question of risk magnitude of such attacks on the power grid is still open: Apart from proof-of-principle examples that require the attacker to have profound knowledge of the system, the risk to real world systems remains largely undetermined. In this paper, we present a vulnerability analysis of a time server used in International Electrotechnical Commission (IEC) 61850-based substations to five GNSS spoofing attacks. We demonstrate that using a GNSS simulator, both quick-conspicuous and slow-stealthy attacks are successful. We assess the difficulty in the scope of a qualitative risk assessment. Our findings can support quantitative risk analysis, and hence decision-makers in ensuring grid stability.


Originalveröffentlichung
DOI: 10.1007/978-3-031-64171-8_28
Scopus
Zitationen: 3
Zugehörige Institution(en) am KIT Institut für Automation und angewandte Informatik (IAI)
Institut für Informationssicherheit und Verlässlichkeit (KASTEL)
Publikationstyp Proceedingsbeitrag
Publikationsjahr 2024
Sprache Englisch
Identifikator ISBN: 978-3-031-64170-1
KITopen-ID: 1000170557
HGF-Programm 46.23.02 (POF IV, LK 01) Engineering Security for Energy Systems
Erschienen in 21st Conference on Detection of Intrusions and Malware and Vulnerability Assessment (DIMVA '24)
Veranstaltung 21st Conference on Detection of Intrusions and Malware and Vulnerability Assessment (DIMVA 2024), Lausanne, Schweiz, 17.07.2024 – 19.07.2024
Verlag Springer
Seiten 545-555
Serie Lecture Notes in Computer Science (LNCS) ; 14828
Vorab online veröffentlicht am 09.07.2024
Nachgewiesen in OpenAlex
Scopus
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