Computation of privacy-preserving prices in smart grids
Fragkiskos Koufogiannis, Shuo Han, George Pappas

Citation
Fragkiskos Koufogiannis, Shuo Han, George Pappas. "Computation of privacy-preserving prices in smart grids". Talk or presentation, 16, September, 2014; Poster presented at the TerraSwarm 2014 Security and Privacy Workshop, Rochester, NY.

Abstract
Demand management through pricing is a modern approach that can improve the efficiency of modern power networks. However, computing optimal prices requires access to data that individuals consider private. We present a novel approach for computing prices while providing privacy guarantees under the differential privacy framework. Differentially private prices are computed through a distributed utility maximization problem with each individual perturbing their own utility function. Privacy concerning temporal localization and monitoring of an individual's activity is enforced in the process. The proposed scheme provides formal privacy guarantees and its performance-privacy trade-off is evaluated quantitatively.

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Citation formats

• HTML

  Fragkiskos Koufogiannis, Shuo Han, George Pappas. <a
  href="http://www.terraswarm.org/pubs/370.html"><i>Computation
  of privacy-preserving prices in smart
  grids</i></a>, Talk or presentation,  16,
  September, 2014; Poster presented at the <a
  href="http://www.terraswarm.org/conferences/14/security/index.htm"
  >TerraSwarm 2014 Security and Privacy Workshop</a>,
  Rochester, NY.

• Plain text

  Fragkiskos Koufogiannis, Shuo Han, George Pappas.
  "Computation of privacy-preserving prices in smart
  grids". Talk or presentation,  16, September, 2014;
  Poster presented at the <a
  href="http://www.terraswarm.org/conferences/14/security/index.htm"
  >TerraSwarm 2014 Security and Privacy Workshop</a>,
  Rochester, NY.

• BibTeX

  @presentation{KoufogiannisHanPappas14_ComputationOfPrivacypreservingPricesInSmartGrids,
      author = {Fragkiskos Koufogiannis and Shuo Han and George
                Pappas},
      title = {Computation of privacy-preserving prices in smart
                grids},
      day = {16},
      month = {September},
      year = {2014},
      note = {Poster presented at the <a
                href="http://www.terraswarm.org/conferences/14/security/index.htm"
                >TerraSwarm 2014 Security and Privacy
                Workshop</a>, Rochester, NY.},
      abstract = {Demand management through pricing is a modern
                approach that can improve the efficiency of modern
                power networks. However, computing optimal prices
                requires access to data that individuals consider
                private. We present a novel approach for computing
                prices while providing privacy guarantees under
                the differential privacy framework. Differentially
                private prices are computed through a distributed
                utility maximization problem with each individual
                perturbing their own utility function. Privacy
                concerning temporal localization and monitoring of
                an individual's activity is enforced in the
                process. The proposed scheme provides formal
                privacy guarantees and its performance-privacy
                trade-off is evaluated quantitatively.},
      URL = {http://terraswarm.org/pubs/370.html}
  }
  

Posted by Fragkiskos Koufogiannis on 18 Sep 2014.
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