Increasing Smart Meter Privacy Through Energy Harvesting and Storage Devices

Smart meters are key elements for the operation of smart grids. By providing near realtime information on the energy consumption of individual users, smart meters increase the efficiency in generation, distribution and storage of energy in a smart grid. The ability of the utility provider to track users' energy consumption inevitably leads to important threats to privacy. In this paper, privacy in a smart metering system is studied from an information theoretic perspective in the presence of energy harvesting and storage units. It is shown that energy harvesting provides increased privacy by diversifying the energy source, while a storage device can be used to increase both the energy efficiency and the privacy of the user. For given input load and energy harvesting rates, it is shown that there exists a trade-off between the information leakage rate, which is used to measure the privacy of the user, and the wasted energy rate, which is a measure of the energy-efficiency. The impact of the energy harvesting rate and the size of the storage device on this trade-off is also studied.

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

[2]  Farrokh Albuyeh,et al.  Grid of the future , 2009, IEEE Power and Energy Magazine.

[3]  Patrick D. McDaniel,et al.  Security and Privacy Challenges in the Smart Grid , 2009, IEEE Security & Privacy.

[4]  Shlomo Shamai,et al.  Information Theoretic Security , 2009, Found. Trends Commun. Inf. Theory.

[5]  Deniz Gündüz,et al.  Smart meter privacy in the presence of an alternative energy source , 2013, 2013 IEEE International Conference on Communications (ICC).

[6]  M. Newborough,et al.  Dynamic energy-consumption indicators for domestic appliances: environment, behaviour and design , 2003 .

[7]  Husheng Li,et al.  Compressed Meter Reading for Delay-Sensitive and Secure Load Report in Smart Grid , 2010, 2010 First IEEE International Conference on Smart Grid Communications.

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

[9]  David P. Varodayan,et al.  Smart meter privacy using a rechargeable battery: Minimizing the rate of information leakage , 2011, 2011 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

[10]  Anno Accademico,et al.  Smart Grid Communications: Overview of research challenges, solutions and standardization activities , 2013 .

[11]  Claude E. Shannon,et al.  Communication theory of secrecy systems , 1949, Bell Syst. Tech. J..

[12]  H. Vincent Poor,et al.  Smart meter privacy in the presence of energy harvesting and storage devices , 2012, 2012 IEEE Third International Conference on Smart Grid Communications (SmartGridComm).

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

[14]  Thomas D. Nicol,et al.  Combating Unauthorized Load Signal Analysis with Targeted Event Masking , 2012, 2012 45th Hawaii International Conference on System Sciences.

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

[16]  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).

[17]  Wei Zeng,et al.  Simulation-Based Computation of Information Rates for Channels With Memory , 2006, IEEE Transactions on Information Theory.

[18]  Ulrich Greveler,et al.  Multimedia Content Identification Through Smart Meter Power Usage Profiles , 2012 .

[19]  H. Vincent Poor,et al.  Smart Meter Privacy: A Theoretical Framework , 2013, IEEE Transactions on Smart Grid.

[20]  Zhu Han,et al.  Coordinated data-injection attack and detection in the smart grid: A detailed look at enriching detection solutions , 2012, IEEE Signal Processing Magazine.

[21]  Thomas M. Cover,et al.  Elements of Information Theory , 2005 .

[22]  Mani B. Srivastava,et al.  Cooperative state estimation for preserving privacy of user behaviors in smart grid , 2011, 2011 IEEE International Conference on Smart Grid Communications (SmartGridComm).

[23]  John Cocke,et al.  Optimal decoding of linear codes for minimizing symbol error rate (Corresp.) , 1974, IEEE Trans. Inf. Theory.

[24]  H. Vincent Poor,et al.  A theory of utility and privacy of data sources , 2010, 2010 IEEE International Symposium on Information Theory.

[25]  H. Y. Lam,et al.  A Novel Method to Construct Taxonomy Electrical Appliances Based on Load Signaturesof , 2007, IEEE Transactions on Consumer Electronics.

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

[27]  H. Vincent Poor,et al.  Smart meter privacy: A utility-privacy framework , 2011, 2011 IEEE International Conference on Smart Grid Communications (SmartGridComm).

[28]  Mani B. Srivastava,et al.  Power management in energy harvesting sensor networks , 2007, TECS.

[29]  H. Vincent Poor,et al.  Utility-Privacy Tradeoffs in Databases: An Information-Theoretic Approach , 2011, IEEE Transactions on Information Forensics and Security.

[30]  Miguel Soriano,et al.  Secure Lossless Aggregation Over Fading and Shadowing Channels for Smart Grid M2M Networks , 2011, IEEE Transactions on Smart Grid.

[31]  H. Poor,et al.  Utility-Privacy Tradeoff in Databases : An Information-theoretic Approach , 2013 .

[32]  Georgios Kalogridis,et al.  Data Mining and Privacy of Personal Behaviour Types in Smart Grid , 2011, 2011 IEEE 11th International Conference on Data Mining Workshops.

[33]  Georgios Kalogridis,et al.  ElecPrivacy: Evaluating the Privacy Protection of Electricity Management Algorithms , 2011, IEEE Transactions on Smart Grid.

[34]  E. Quinn.  Privacy and the New Energy Infrastructure , 2009 .

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

[36]  G. W. Hart,et al.  Nonintrusive appliance load monitoring , 1992, Proc. IEEE.

[37]  Michael Backes,et al.  Differentially Private Smart Metering with Battery Recharging , 2013, DPM/SETOP.