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Consumer Privacy on Distributed Energy Markets

  • Niklas BüscherEmail author
  • Stefan Schiffner
  • Mathias Fischer
Conference paper
  • 1.1k Downloads
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9857)

Abstract

Recently, several privacy-enhancing technologies for smart grids have been proposed. However, most of these solutions presume the cooperation of all smart grid participants. Hence, the privacy protection of consumers depends on the willingness of the suppliers to deploy privacy-enhancing technologies. Since electrical energy is essential for our modern life, it is impossible for consumers to opt out. We propose a novel consumer-only (do-it-yourself) privacy-enhancing approach under the assumption that users can obtain their energy from multiple suppliers on a distributed market. By splitting the demand over multiple suppliers, the information each of them can collect about a single consumer is reduced. In this context, we suggest two different buying strategies: a time and a sample diversification strategy. To measure their provided level of privacy protection, we introduce a new indistinguishability metric \(\lambda \)-Indistinguishability (\(\lambda \text {-IND}\)) that measures how relative consumption changes can be hidden in the total consumption. We evaluate the presented strategies with \(\lambda \text {-IND}\) and derive first privacy boundaries. The evaluation of our buying strategies on real-world energy data sets indicates their ability to hide load profiles of privacy sensitive appliances at low communication and computational overhead.

Keywords

Smart Grid Privacy Protection Load Sample Statistical Distance Load Profile 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgments

This work has been co-funded by the German Federal Ministry of Education and Research (BMBF) within CRISP, by the DFG as part of project A.1 within the RTG 2050 “Privacy and Trust for Mobile Users” and by the Hessian LOEWE excellence initiative within CASED. At the time this research was conducted, Stefan Schiffner and Mathias Fischer were part of CASED at TU Darmstadt. Stefan Schiffner is currently employed at the European Union Agency for Network and Information Security (ENISA). The content of this article does not reflect the official opinion of ENISA. Responsibility for the information and views expressed in therein lies entirely with the authors.

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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Niklas Büscher
    • 1
    Email author
  • Stefan Schiffner
    • 2
  • Mathias Fischer
    • 3
  1. 1.Technische Universität DarmstadtDarmstadtGermany
  2. 2.ENISAAthensGreece
  3. 3.Westfälische Wilhelms-Universität MünsterMünsterGermany

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