Authors:
Fabian Knirsch
1
;
Dominik Engel
1
;
Christian Neureiter
1
;
Marc Frincu
2
and
Viktor Prasanna
2
Affiliations:
1
Salzburg University of Applied Sciences, Austria
;
2
University of Southern California, United States
Keyword(s):
Smart Grid, Privacy, Model-based, Assessment.
Related
Ontology
Subjects/Areas/Topics:
Information and Systems Security
;
Privacy Enhancing Technologies
Abstract:
In a smart grid, data and information are transported, transmitted, stored, and processed with various stakeholders
having to cooperate effectively. Furthermore, personal data is the key to many smart grid applications
and therefore privacy impacts have to be taken into account. For an effective smart grid, well integrated solutions
are crucial and for achieving a high degree of customer acceptance, privacy should already be considered
at design time of the system. To assist system engineers in early design phase, frameworks for the automated
privacy evaluation of use cases are important. For evaluation, use cases for services and software architectures
need to be formally captured in a standardized and commonly understood manner. In order to ensure this common
understanding for all kinds of stakeholders, reference models have recently been developed. In this paper
we present a model-driven approach for the automated assessment of such services and software architectures
in the smart
grid that builds on the standardized reference models. The focus of qualitative and quantitative
evaluation is on privacy. For evaluation, the framework draws on use cases from the University of Southern
California microgrid.
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