Issue |
EPJ Web Conf.
Volume 217, 2019
International Workshop on Flexibility and Resiliency Problems of Electric Power Systems (FREPS 2019)
|
|
---|---|---|
Article Number | 01008 | |
Number of page(s) | 7 | |
DOI | https://doi.org/10.1051/epjconf/201921701008 | |
Published online | 15 October 2019 |
https://doi.org/10.1051/epjconf/201921701008
Trust in control: a trust model for power system network assessment
1
OFFIS – Institute for Information Technology, Energy Division, Escherweg 2, 26121 Oldenburg, Germany
2
Salzburg University of Applied Sciences, Center for Secure Energy Informatics, Urstein Süd 1, 5412 Puch bei Hallein, Austria
* Corresponding author: michael.brand@offis.de
Published online: 15 October 2019
The question of whether a process variable transmitted from a device in the field to a power system control center is trustworthy is of high importance nowadays. Traditional bad data detection schemes have their limits in cases of elaborated cyberattacks and cascading failures in a system of systems such as a digitalized power system. This paper proposes a trust model designed for power system network assessment (PSNA). Different to other domains, where trust models already exist (e.g., OC-Trust for organic computing systems), the environment for PSNA is more centralized, and the focus lies on other facets than in organic computing due to the nature of the environment. Therefore, OC-Trust is tailored by categorizing its facets regarding their relevance for PSNA on the one hand. On the other hand, the trust model is extended to realize context-sensitive intersections of trust values. Furthermore, an example of an instantiation of the resulting PSNA-Trust model is given. Two security metrics and one credibility metric based on literature are presented as well as an equation for a context-sensitive intersection.
© The Authors, published by EDP Sciences, 2019
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.