TY - JOUR
T1 - Differential privacy for real smart metering data
AU - Eibl, G.
AU - Engel, D.
N1 - Cited By :51
Export Date: 14 December 2023
Correspondence Address: Eibl, G.; Josef Ressel Center for User-Centric Smart Grid Privacy, Urstein Süd 1, Puch, Austria; email: [email protected]
Funding details: Bundesministerium für Bildung, Wissenschaft und Forschung, BMBWF
Funding text 1: Open access funding provided by FH Salzburg - University of Applied Sciences. The financial support by the Austrian Federal Ministry of Science, Research and Education and the Austrian National Foundation for Research, Technology and Development is gratefully acknowledged.
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PY - 2017
Y1 - 2017
N2 - The collection of detailed consumption data through smart metering has led to privacy concerns. Aggregating the consumption data over a number of smart meters can be used to strike a balance between functional and privacy requirements. A number of contributions have proposed the use of differential privacy in smart metering to perturb aggregates in order to provide a proven privacy property for end consumers. However, as differential privacy has originally been proposed for very large datasets, the applicability in real-world smart metering is not guaranteed. In this paper, the effect of differential privacy on real smart metering data is studied, especially with respect to balancing utility and privacy requirements. The main finding is that even after some improvements of the basic method the aggregation group size must be of the order of thousands of smart meters in order to have reasonable utility. © 2016, The Author(s).
AB - The collection of detailed consumption data through smart metering has led to privacy concerns. Aggregating the consumption data over a number of smart meters can be used to strike a balance between functional and privacy requirements. A number of contributions have proposed the use of differential privacy in smart metering to perturb aggregates in order to provide a proven privacy property for end consumers. However, as differential privacy has originally been proposed for very large datasets, the applicability in real-world smart metering is not guaranteed. In this paper, the effect of differential privacy on real smart metering data is studied, especially with respect to balancing utility and privacy requirements. The main finding is that even after some improvements of the basic method the aggregation group size must be of the order of thousands of smart meters in order to have reasonable utility. © 2016, The Author(s).
KW - Aggregation
KW - Differential privacy
KW - Smart metering
KW - Agglomeration
KW - Electric measuring instruments
KW - Smart meters
KW - Differential privacies
KW - End consumers
KW - Group size
KW - Large datasets
KW - Privacy concerns
KW - Privacy requirements
KW - Real-world
KW - Data privacy
U2 - 10.1007/s00450-016-0310-y
DO - 10.1007/s00450-016-0310-y
M3 - Article
SN - 1865-2034
VL - 32
SP - 173
EP - 182
JO - Comput. Sci. Res. Devel. Dev.
JF - Comput. Sci. Res. Devel. Dev.
IS - 1-2
ER -
SDG 7 Affordable and Clean Energy