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
Link To Document :
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