• DocumentCode
    56919
  • Title

    Privacy-preserving data aggregation in smart metering systems: an overview

  • Author

    Erkin, Zekeriya ; Troncoso-Pastoriza, J.R. ; Lagendijk, R.L. ; Perez-Gonzalez, F.

  • Author_Institution
    Mediamatics, Tech. Univ. Delft, Delft, Netherlands
  • Volume
    30
  • Issue
    2
  • fYear
    2013
  • fDate
    Mar-13
  • Firstpage
    75
  • Lastpage
    86
  • Abstract
    Growing energy needs are forcing governments to look for alternative resources and ways to better manage the energy grid and load balancing. As a major initiative, many countries including the United Kingdom, United States, and China have already started deploying smart grids. One of the biggest advantages of smart grids compared to traditional energy grids is the ability to remotely read fine-granular measurements from each smart meter, which enables the grid operators to balance load efficiently and offer adapted time-dependent tariffs. However, collecting fine-granular data also poses a serious privacy threat for the citizens as illustrated by the decision of the Dutch Parliament in 2009 that rejects the deployment of smart meters due to privacy considerations. Hence, it is a must to enforce privacy rights without disrupting the smart grid services like billing and data aggregation. Secure signal processing (SSP) aims at protecting the sensitive data by means of encryption and provides tools to process them under encryption, effectively addressing the smart metering privacy problem.
  • Keywords
    data privacy; power engineering computing; power meters; power system measurement; power system protection; resource allocation; signal processing; smart meters; smart power grids; China; Dutch Parliament; SSP; United Kingdom; United States; encryption; energy grid; fine-granular data; load balancing; privacy-preserving data aggregation; secure signal processing; smart grid services; smart metering privacy problem; Data aggregation; Data privacy; Electricity supply industry; Encryption; Energy management; Environmental factors; Privacy; Smart grids; Smart meters;
  • fLanguage
    English
  • Journal_Title
    Signal Processing Magazine, IEEE
  • Publisher
    ieee
  • ISSN
    1053-5888
  • Type

    jour

  • DOI
    10.1109/MSP.2012.2228343
  • Filename
    6461626