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The impact of privacy-enhancing technologies on the quality of services on power grid systems

February 6th, 2023

Thesis Type
  • Master
Status
Open
Supervisor(s)
Stefan Decker
Advisor(s)
Mehdi Akbari G.
osen
Contact
mehdi.akbari.gurabi@fit.fraunhofer.de
oemer.sen@fit.fraunhofer.de

The task is an investigation of best practices and standards in the security of industrial control systems and power grid systems to find use cases for enabling privacy-enhancing technologies for Machine learning functions, for example, load forecasting. Different mechanisms should be investigated, and metrics applicable to the use cases should be defined; for example, the usability of the service should be defined by metrics. For the practical part, a minimalistic environment for simulating power grids and communications should be utilized, such as the Pandapower package. Different components of the project that should be implemented will be the minimal power grid simulators based on power grid models, communication simulators, simulation of Advanced metering infrastructure services and ML-based functions and PETs. Then assess the quality of impact for the use cases for AMI services.

Some literature related to the topic:


Prerequisites:

Basic knowledge in the domains of cyber security.