Abstract
New technologies for computerized metering and data collection in the electrical power grid promise to create a more efficient, cost-effective, and adaptable smart grid. However, naive implementations of smart grid data collection could jeopardize the privacy of consumers, and concerns about privacy are a significant obstacle to the rollout of smart grid technology. Our work proposes a design for a smart metering system that will allow utilities to use the collected data effectively while preserving the privacy of individual consumers.
- André Allavena, Alan Demers, and John E. Hopcroft. Correctness of a gossip based membership protocol. In Proceedings of the Twenty-fourth Annual ACM Symposium on Principles of Distributed Computing, PODC '05, pages 292--301, New York, NY, USA, 2005. ACM. Google ScholarDigital Library
- Ross Anderson and Shailendra Fuloria. On the security economics of electricity metering. In The Ninth Workshop on the Economics of Information Security (WEIS 2010), Harvard University, 2010. Citeseer.Google Scholar
- Ken Birman, Márk Jelasity, Robert Kleinberg, and Edward Tremel. A secure communications overlay for privacy-preserving distributed computation. 2014. Submitted for publication. Preliminary version available upon request.Google Scholar
- Kenneth P. Birman, Mark Hayden, Oznur Ozkasap, Zhen Xiao, Mihai Budiu, and Yaron Minsky. Bimodal multicast. ACM Trans. Comput. Syst., 17(2):41--88, 1999. Google ScholarDigital Library
- Edward Bortnikov, Maxim Gurevich, Idit Keidar, Gabriel Kliot, and Alexander Shraer. Brahms: Byzantine resilient random membership sampling. In Proc. 27th ACM Symp. on Principles of Distributed Computing, PODC '08, page 145--154. ACM, 2008. Google ScholarDigital Library
- Ruichuan Chen, Istemi Ekin Akkus, and Paul Francis. SplitX: High-performance private analytics. In Proc. ACM SIGCOMM, page 315--326. ACM, 2013. Google ScholarDigital Library
- Chris Clifton, Murat Kantarcioglu, Jaideep Vaidya, Xiaodong Lin, and Michael Y. Zhu. Tools for privacy preserving distributed data mining. SIGKDD Explor. Newsl., 4(2):28--34, December 2002. Google ScholarDigital Library
- Alan Demers, Dan Greene, Carl Hauser, Wes Irish, John Larson, Scott Shenker, Howard Sturgis, Dan Swinehart, and Doug Terry. Epidemic algorithms for replicated database maintenance. In Proc. 6th Annual ACM Symp. on Principles of Distributed Computing, PODC '87, page 112. ACM, 1987. Google ScholarDigital Library
- John R. Douceur. The sybil attack. In Peter Druschel, Frans Kaashoek, and Antony Rowstron, editors, Peer-to-Peer Systems, number 2429 in LNCS, pages 251--260. Springer, 2002. Google ScholarDigital Library
- Cynthia Dwork. A firm foundation for private data analysis. Commun. ACM, 54(1):86--95, January 2011. Google ScholarDigital Library
- Cynthia Dwork, Krishnaram Kenthapadi, Frank McSherry, Ilya Mironov, and Moni Naor. Our data, ourselves: Privacy via distributed noise generation. In Serge Vaudenay, editor, Advances in Cryptology - EUROCRYPT 2006, number 4004 in Lecture Notes in Computer Science, pages 486--503. Springer Berlin Heidelberg, January 2006. Google ScholarDigital Library
- P. Th. Eugster, R. Guerraoui, S. B. Handurukande, P. Kouznetsov, and A.-M. Kermarrec. Lightweight probabilistic broadcast. ACM Trans. Comput. Syst., 21:341--374, 2003. Google ScholarDigital Library
- Márk Jelasity and Kenneth P. Birman. Distributional differential privacy for large-scale smart metering. In Proceedings of the 2nd ACM Workshop on Information Hiding and Multimedia Security, IH&MMSec '14, pages 141--146, New York, NY, USA, 2014. ACM. Google ScholarDigital Library
- Gian Paolo Jesi, Alberto Montresor, and Maarten van Steen. Secure peer sampling. Computer Networks, 54(12):2086--2098, 2010. Google ScholarDigital Library
- D. Kempe, A. Dobra, and J. Gehrke. Gossip-based computation of aggregate information. In 44th Annual IEEE Symp. on Foundations of Comp. Science, pages 482--491, 2003. Google ScholarDigital Library
- C. Laughman, Kwangduk Lee, R. Cox, S. Shaw, S. Leeb, L. Norford, and P. Armstrong. Power signature analysis. IEEE Power and Energy Magazine, 1(2):56--63, March 2003.Google ScholarCross Ref
- Harry C. Li, Allen Clement, Edmund L. Wong, Jeff Napper, Indrajit Roy, Lorenzo Alvisi, and Michael Dahlin. BAR gossip. In Proc. 7th Symp. on Operating Systems Design and Implementation, OSDI '06, pages 191--204. USENIX Association, 2006. Google ScholarDigital Library
- Mikhail Lisovich and Stephen Wicker. Privacy concerns in upcoming residential and commercial demand-response systems. In Proc. of the Clemson University Power Systems Conference, Clemson University, March 2008. Citeseer.Google Scholar
- Patrick McDaniel and Stephen McLaughlin. Security and privacy challenges in the smart grid. IEEE Security and Privacy, 7(3):75--77, May 2009. Google ScholarDigital Library
- Amir-Hamed Mohsenian-Rad, Vincent W.S. Wong, Juri Jatskevich, Robert Schober, and Alberto Leon-Garcia. Autonomous demand-side management based on game-theoretic energy consumption scheduling for the future smart grid. IEEE Transactions on Smart Grid, 1(3):320--331, December 2010.Google ScholarCross Ref
- Róbert Ormándi, István Heged?us, and Márk Jelasity. Gossip learning with linear models on fully distributed data. Concurrency and Computation: Practice and Experience, 25(4):556--571, 2013.Google ScholarCross Ref
- Jukka V. Paatero and Peter D. Lund. A model for generating household electricity load profiles. International Journal of Energy Research, 30(5):273--290, April 2006.Google ScholarCross Ref
- Alfredo Rial and George Danezis. Privacy-preserving smart metering. In Proceedings of the 10th Annual ACM Workshop on Privacy in the Electronic Society, WPES '11, page 49--60, New York, NY, USA, 2011. ACM. Google ScholarDigital Library
- G. Pascal Zachary. Saving smart meters from a backlash. IEEE Spectrum, 48(8):8-8, August 2011.Google ScholarDigital Library
Index Terms
- Building a Secure and Privacy-Preserving Smart Grid
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