Model-driven Privacy Assessment in the Smart Grid
- Salzburg Univ. (Austria); Power System Information & Advanced Technologies LADWP Power System Engineering Division
- Salzburg Univ. (Austria)
- Univ. of Southern California, Los Angeles, CA (United States)
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.
- Research Organization:
- City of Los Angeles Department, CA (United States)
- Sponsoring Organization:
- USDOE Office of Electricity Delivery and Energy Reliability (OE)
- DOE Contract Number:
- OE0000192
- OSTI ID:
- 1332332
- Report Number(s):
- DOE-USC--00192-76
- Country of Publication:
- United States
- Language:
- English
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