Elderberry: A peer-to-peer, privacy-aware smart metering protocol

The deployment of smart metering provides an immense amount of data for power grid operators and energy providers. By using this data, a more efficient and flexible power grid can be realized. However, this data also raises privacy concerns since it contains very sensitive information about customers. In this paper, we present Elderberry, a peer-to-peer protocol that enables near real-time smart metering while preserving the customer's privacy. By forming small groups of cooperating smart meters, their consumption traces are anonymized before being aggregated and sent to the grid operator. Through aggregation, Elderberry realizes efficient monitoring of large numbers of smart meters. It reaches this goal without computationally complex cryptography and adds only little communication overhead.

[1]  Patrick D. McDaniel,et al.  Protecting consumer privacy from electric load monitoring , 2011, CCS '11.

[2]  Georgios Kalogridis,et al.  Affordable Privacy for Home Smart Meters , 2011, 2011 IEEE Ninth International Symposium on Parallel and Distributed Processing with Applications Workshops.

[3]  Christoph Sorge,et al.  Do not snoop my habits: preserving privacy in the smart grid , 2012, IEEE Communications Magazine.

[4]  Bart Jacobs,et al.  Privacy-Friendly Energy-Metering via Homomorphic Encryption , 2010, STM.

[5]  Ben Y. Zhao,et al.  Towards a Common API for Structured Peer-to-Peer Overlays , 2003, IPTPS.

[6]  Ralf Steinmetz,et al.  Monitoring and management of structured peer-to-peer systems , 2009, 2009 IEEE Ninth International Conference on Peer-to-Peer Computing.

[7]  Rudolf Hornig,et al.  An overview of the OMNeT++ simulation environment , 2008, Simutools 2008.

[8]  Georgios Kalogridis,et al.  Smart Grid Privacy via Anonymization of Smart Metering Data , 2010, 2010 First IEEE International Conference on Smart Grid Communications.

[9]  Dirk Westhoff,et al.  Homomorphic Primitives for a Privacy-friendly Smart Metering Architecture , 2012, SECRYPT.

[10]  S. Krause,et al.  OverSim: A Flexible Overlay Network Simulation Framework , 2007, 2007 IEEE Global Internet Symposium.

[11]  Christoph Sorge,et al.  A Privacy Model for Smart Metering , 2010, 2010 IEEE International Conference on Communications Workshops.

[12]  Georgios Kalogridis,et al.  Privacy for Smart Meters: Towards Undetectable Appliance Load Signatures , 2010, 2010 First IEEE International Conference on Smart Grid Communications.

[13]  Peng Liu,et al.  Secure and privacy-preserving information aggregation for smart grids , 2011, Int. J. Secur. Networks.

[14]  A. Prudenzi,et al.  A neuron nets based procedure for identifying domestic appliances pattern-of-use from energy recordings at meter panel , 2002, 2002 IEEE Power Engineering Society Winter Meeting. Conference Proceedings (Cat. No.02CH37309).

[15]  Steven B. Leeb,et al.  Power signature analysis , 2003 .

[16]  Xue Liu,et al.  PDA: Privacy-Preserving Data Aggregation in Wireless Sensor Networks , 2007, IEEE INFOCOM 2007 - 26th IEEE International Conference on Computer Communications.