Many smart metering proposals threaten users' privacy by disclosing fine-grained consumption data to utilities. We have designed protocols that allow for precise billing of consumption while not revealing any consumption information to third parties. We also have developped protocols that allow for privacy-friendly real-time aggregation of smart-meter readings.
Information computed on the basis of fine-grained smart-meter readings has multiple uses within the energy industry, including billing, providing energy advice, settlement, forecasting, demand response, and fraud detection. Microsoft Research has developed technologies that allow for these computations to be executed without the need for customers to disclose raw meter readings. In brief, smart-meters transmit encrypted certified meter readings, that are processed by any customer device (smart phone, web browser, home gateway, personal computer) to compute the information required, and further provide them to authorised parties. These privacy-friendly computations can include time-of-use bills, settlement values, fraud detection flags, or usage profiles. Cryptographic mechanisms protect the privacy of the data and the correctness of the computations even when performed on customer devices.
Energy industry processes, such as settlement, monitoring, financial forecasting, transmission network development or demand response, require real-time aggregates of readings across populations of meters. Microsoft Research has developed privacy technologies that allow the direct aggregation of encrypted meter readings. The sum of readings, as well as their mean and variance, can be computed in real-time, without revealing individual meter readings.
Our protocols are generic enough to be used in other settings such as pay-as-you-drive car insurance, electronic traffic pricing and on-line services billing.
- Exec summary:
- White papers & presentations:
- Academic Publications:
- Alfredo Rial and George Danezis. Privacy-Preserving Smart Metering. Proceedings of the 2011 ACM Workshop on Privacy in the Electronic Society, WPES 2011, Chicago, USA, October 17, 2008.
- Klaus Kursawe, George Danezis, Markulf Kohlweiss: Privacy-Friendly Aggregation for the Smart-Grid. Privacy Enhancing Technologies - 11th International Symposium, PETS 2011, Waterloo, ON, Canada, July 27-29, 2011. ISBN 978-3-642-22262-7: pages 175-191.
- George Danezis, Markulf Kohlweiss, and Alfredo Rial. Differentially Private Billing with Rebates. Information Hiding, IH2011, LNCS 6958: pages 148-162.
- Technical Reports:
- Marek Jawurek, Florian Kerschbaum, and George Danezis. Privacy Technologies for Smart Grids - A Survey of Options. MSR-TR-2012-119. November 2012
- Andres Molina-Markham and George Danezis and Kevin Fu and Prashant Shenoy and David Irwin. Designing Privacy-preserving Smart Meters with Low-cost Microcontrollers. Cryptology ePrint Archive: Report 2011/544. 3 Oct 2011.
- Alfredo Rial & George Danezis. Privacy-friendly smart metering. Microsoft Research Technical Report MSR-TR-2010-150. November 19, 2010.
- George Danezis, Markulf Kohlweiss, and Alfredo Rial. Differentially Private Billing with Rebates. Microsoft Research Technical Report MSR-TR-2011-10. February 2011.
- Klaus Kursawe, Markulf Kohlweiss, George Danezis. Privacy-friendly Aggregation for the Smart-grid. Microsoft Research Tech Report, March 2011.
- Nikhil Swamy, Juan Chen, Cedric Fournet, Karthikeyan Bharagavan, and Jean Yang. Security Programming with Refinement Types and Mobile Proofs. Microsoft Research Technical Report MSR-TR-2010-149. November 2010.