MASKER: Masking for privacy-preserving aggregation in the smart grid ecosystem

MASKER: Masking for privacy-preserving aggregation in the smart grid ecosystem The introduction of information and communication technologies to the traditional energy grid offers advantages like efficiency, increased reliability, resilience and better control of demand-response, while on the other hand poses customers' privacy at risk. Aggregation of electricity consumption readings in intermediate nodes is needed for efficient network utilisation; however, by using information collected by a smart meter, an attacker can deduce whether a house is empty from its residents, which devices are being used, residents' habits and so on. Here, we propose a privacy-preserving aggregation protocol that obfuscates individual consumption readings, while at the same time allows their aggregation without loss of accuracy. The same protocol is easily extensible to support privacy-preserving customer billing as well. Our solution is lightweight and presents additive homomorphic properties based on standard and easy to implement cryptographic operations, while it does not require an always available trusted third party for its operation. Finally, we show that knowledge of the obfuscated values does not affect customer privacy, since they cannot reveal enough information for an attacker to infer real consumption values. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Computers & Security Elsevier

MASKER: Masking for privacy-preserving aggregation in the smart grid ecosystem

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Publisher
Elsevier
Copyright
Copyright © 2017 Elsevier Ltd
ISSN
0167-4048
D.O.I.
10.1016/j.cose.2017.11.008
Publisher site
See Article on Publisher Site

Abstract

The introduction of information and communication technologies to the traditional energy grid offers advantages like efficiency, increased reliability, resilience and better control of demand-response, while on the other hand poses customers' privacy at risk. Aggregation of electricity consumption readings in intermediate nodes is needed for efficient network utilisation; however, by using information collected by a smart meter, an attacker can deduce whether a house is empty from its residents, which devices are being used, residents' habits and so on. Here, we propose a privacy-preserving aggregation protocol that obfuscates individual consumption readings, while at the same time allows their aggregation without loss of accuracy. The same protocol is easily extensible to support privacy-preserving customer billing as well. Our solution is lightweight and presents additive homomorphic properties based on standard and easy to implement cryptographic operations, while it does not require an always available trusted third party for its operation. Finally, we show that knowledge of the obfuscated values does not affect customer privacy, since they cannot reveal enough information for an attacker to infer real consumption values.

Journal

Computers & SecurityElsevier

Published: Mar 1, 2018

References

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