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Expert-Guided Security Risk Assessment of Evolving Power Grids
Aalto Univ, Sch Elect Engn, Dept Commun & Networking, Espoo 02150, Finland..
KTH, School of Electrical Engineering and Computer Science (EECS), Electrical Engineering, Electric Power and Energy Systems. Aalto Univ, Sch Elect Engn, Dept Commun & Networking, Espoo 02150, Finland..
KTH, School of Electrical Engineering and Computer Science (EECS), Electrical Engineering, Electric Power and Energy Systems.ORCID iD: 0000-0003-4763-9429
Aalto Univ, Sch Elect Engn, Dept Commun & Networking, Espoo 02150, Finland..
2022 (English)In: Energies, E-ISSN 1996-1073, Vol. 15, no 9, p. 3237-, article id 3237Article in journal (Refereed) Published
Abstract [en]

Electric power grids, which form an essential part of the critical infrastructure, are evolving into highly distributed, dynamic networks in order to address the climate change. This fundamental transition relies on extensive automation solutions based on communications and information technologies. Thus, it also gives rise to new attack points for malicious actors and consequently, increases the vulnerability of the electric energy system. This study presents a qualitative assessment of power grid cybersecurity through expert interviews across countries in Europe and the U.S. to gain understanding of the latest developments and trends in the cybersecurity of future electric energy systems. The horizon of the assessment is 10 years spanning until the early 2030s. Thereafter, the study identifies how and to which extent the risks identified to be most significant are understood and addressed in the latest research and industry publications aiming at identifying areas deserving specific further attention. The most significant threats based on the assessment are False Data Injection (FDI), Denial of Service (DoS) supply chain, and ransomware and malware attacks.

Place, publisher, year, edition, pages
MDPI AG , 2022. Vol. 15, no 9, p. 3237-, article id 3237
Keywords [en]
smart grids, power grids, cybersecurity, security risk assessment
National Category
Other Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
URN: urn:nbn:se:kth:diva-313050DOI: 10.3390/en15093237ISI: 000794482600001Scopus ID: 2-s2.0-85129724090OAI: oai:DiVA.org:kth-313050DiVA, id: diva2:1662290
Note

QC 20220531

Available from: 2022-05-31 Created: 2022-05-31 Last updated: 2024-03-15Bibliographically approved

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Gopalakrishnan, PavithraBertling Tjernberg, Lina

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