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Two Is Not Enough: Privacy Assessment of Aggregation Schemes in Smart Metering

Büscher, Niklas ; Boukoros, Spyros ; Bauregger, Stefan ; Katzenbeisser, Stefan (2017)
Two Is Not Enough: Privacy Assessment of Aggregation Schemes in Smart Metering.
Minneapolis, USA
doi: 10.1515/popets-2017-0030
Conference or Workshop Item, Bibliographie

Abstract

The widespread deployment of smart meters that frequently report energy consumption information, is a known threat to consumers’ privacy. Many promising privacy protection mechanisms based on secure aggregation schemes have been proposed. Even though these schemes are cryptographically secure, the energy provider has access to the plaintext aggregated power consumption. A privacy trade-off exists between the size of the aggregation scheme and the personal data that might be leaked, where smaller aggregation sizes leak more personal data. Recently, a UK industrial body has studied this privacy trade-off and identified that two smart meters forming an aggregate, are sufficient to achieve privacy. In this work, we challenge this study and investigate which aggregation sizes are sufficient to achieve privacy in the smart grid. Therefore, we propose a flexible, yet formal privacy metric using a cryptographic game based definition. Studying publiclyavailable, real world energy consumption datasets with various temporal resolutions, ranging from minutes to hourly intervals, we show that a typical household can be identified with very high probability. For example, we observe a 50% advantage over random guessing in identifying households for an aggregation size of 20 households with a 15-minutes reporting interval. Furthermore, our results indicate that single appliances can be identified with significant probability in aggregation sizes up to 10 households.

Item Type: Conference or Workshop Item
Erschienen: 2017
Creators: Büscher, Niklas ; Boukoros, Spyros ; Bauregger, Stefan ; Katzenbeisser, Stefan
Type of entry: Bibliographie
Title: Two Is Not Enough: Privacy Assessment of Aggregation Schemes in Smart Metering
Language: English
Date: July 2017
Publisher: De Gruyter
Issue Number: 4
Book Title: Proceedings on Privacy Enhancing Technologies
Series Volume: 2017
Event Location: Minneapolis, USA
DOI: 10.1515/popets-2017-0030
Abstract:

The widespread deployment of smart meters that frequently report energy consumption information, is a known threat to consumers’ privacy. Many promising privacy protection mechanisms based on secure aggregation schemes have been proposed. Even though these schemes are cryptographically secure, the energy provider has access to the plaintext aggregated power consumption. A privacy trade-off exists between the size of the aggregation scheme and the personal data that might be leaked, where smaller aggregation sizes leak more personal data. Recently, a UK industrial body has studied this privacy trade-off and identified that two smart meters forming an aggregate, are sufficient to achieve privacy. In this work, we challenge this study and investigate which aggregation sizes are sufficient to achieve privacy in the smart grid. Therefore, we propose a flexible, yet formal privacy metric using a cryptographic game based definition. Studying publiclyavailable, real world energy consumption datasets with various temporal resolutions, ranging from minutes to hourly intervals, we show that a typical household can be identified with very high probability. For example, we observe a 50% advantage over random guessing in identifying households for an aggregation size of 20 households with a 15-minutes reporting interval. Furthermore, our results indicate that single appliances can be identified with significant probability in aggregation sizes up to 10 households.

Uncontrolled Keywords: smart grid, smart meters, privacy, aggrega- tion, measurements, privacy metric
Identification Number: TUD-CS-2017-0213
Divisions: 20 Department of Computer Science
20 Department of Computer Science > Security Engineering
DFG-Graduiertenkollegs
DFG-Graduiertenkollegs > Research Training Group 2050 Privacy and Trust for Mobile Users
Profile Areas
Profile Areas > Cybersecurity (CYSEC)
Date Deposited: 07 Aug 2017 13:42
Last Modified: 22 Jan 2019 11:09
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