Model-Free Detection of Cyberattacks on Voltage Control in Distribution Grids
Paper i proceeding, 2019

Incorporating information and communication technology in the operation of the electricity grid is undoubtedly contributing to a more cost-efficient, controllable, and flexible power grid. Although this technology is promoting flexibility and convenience, its integration with the electricity grid is rendering this critical infrastructure inherently vulnerable to cyberattacks that have potential to cause large-scale and far-reaching damage. In light of the growing need for a resilient smart grid, developing suitable security mechanisms has become a pressing matter. In this work, we investigate the effectiveness of a model-free state-of-the-art attack-detection method recently proposed by the cybersecurity community in detecting common types of cyberattacks on voltage control in distribution grids. Experimental results show that, by monitoring raw controller and smart-meter data in real time, it is possible to detect denial of service, replay, and integrity attacks, thus contributing to a resilient and more secure grid.

Smart Grid

Model-Free Detection

Cyberattack

Low-Voltage Grid

PASAD

Författare

Mohammed S. Kemal

Aalborg Universitet

Wissam Aoudi

Chalmers, Data- och informationsteknik, Nätverk och system

Rasmus L. Olsen

Aalborg Universitet

Magnus Almgren

Chalmers, Data- och informationsteknik, Nätverk och system

Hans-Peter Schwefel

Aalborg Universitet

15th European Dependable Computing Conference

15th European Dependable Computing Conference
Naples, Italy,

Säkra IT-system för drift och övervakning av samhällskritisk infrastruktur

Myndigheten för samhällsskydd och beredskap, 2015-09-01 -- 2020-08-31.

Integrated cyber-physical solutions for intelligent distribution grid with high penetration of renewables (UNITED-GRID)

Europeiska kommissionen (Horisont 2020), 2017-11-01 -- 2020-04-30.

Styrkeområden

Informations- och kommunikationsteknik

Energi

Drivkrafter

Hållbar utveckling

Ämneskategorier

Datavetenskap (datalogi)

DOI

10.1109/EDCC.2019.00041

Mer information

Senast uppdaterat

2020-06-02