Privacy-preserving smart metering

Smart meters are being introduced in order to: (i) allow utilities to continuously monitor the distribution network, and (ii) enable new generation of energy services in residential as well as non-residential buildings. At the granularity of a city, smart meter data will be a crucial component of the value networks that can achieve energy efficiency at scale. However, the analysis of smart meter data, especially in residential buildings, reveals information that used to be hidden, and introduces completely new data flows and even actors in the context of energy services. This raises new concerns in terms of privacy [Danezis, Dillahunt10, KatzenBeisser11, Lam07, Molina10, Mulligan11, Nissenbaum10, Patel07]. In particular, at the 1Hz granularity provided by EDF’s Linky, electrical appliances have a distinctive energy signature and it is possible to infer people’s activities at home from smart meter data [Dillahunt10, Lam07, Mulligan11]. In light of the above, the question is how to provide advanced personal energy services while preserving the privacy of the persons involved?  The goal is to have a positive impact on the deployment of the Linky ( in France and to contribute to the establishment of a smart city value network around smart meter data that offers strong privacy guarantees. This work builds upon the vision of trusted cells developed by the SMIS team.

References :

[Danezis] G. Danezis, Privacy Technology Options for Smart Metering. Microsoft Research White Paper.

[Dillahunt10] T. Dillahunt, J. Mankoff, Understanding conflict between landlords and tenants: Implications for energy sensing and feedback. Ubicomp, 2010.

[Katzenbeisser11] S. Katzenbeisser, K. Kursawe, Privacy and Security in Smart Energy Grids. Dagstuhl Seminar 1151. 2011.

[Lam07] H. Lam. A Novel Method to Construct Taxonomy Electrical Appliances Based on Load Signatures. IEEE Transactions on Consumer Electronics, 2007.

[Molina10] A. Molina-Markham, P. Shenoy. Private memoirs of a smart meter. Proceedings of BuildSys’10. 2010.

[Mulligan11] A. D. K. Mulligan, L. Wang, A. J. Burstein. Final Project Report Privacy in the Smart Grid: An Information Flow Analysis. CIEE Report. 2011.

[Nissenbaum10] H. Nissenbaum. Privacy in context: Technology, policy, and the integrity of social life, Stanford Law Books, 2010.

[Patel07] S. Patel, T. Robertson. At the flick of a switch: Detecting and classifying unique electrical events on the residential power line. Ubicomp, 2007.

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