@article{97767608779b4f8ba483e7425c83b825,
title = "Error-Resilient Masking Approaches for Privacy Preserving Data Aggregation",
abstract = "The deployment of future energy systems promises a number of advantages for a more stable and reliable grid as well as for a sustainable usage of energy resources. The efficiency and effectiveness of such smart grids rely on customer consumption data that is collected, processed, and analyzed. This data is used for billing, monitoring, and prediction. However, this implies privacy threats. Approaches exist that aim to either encrypt data in certain ways, to reduce the resolution of data or to mask data in a way so that an individuals' contribution is untraceable. While the latter is an effective way for protecting customer privacy when aggregating over space or time, one of the drawbacks of these approaches is the limitation or full negligence of device failures. In this paper, we therefore propose a masking approach for spatio-temporal aggregation of time series for protecting individual privacy while still providing sufficient error-resilience and reliability. {\textcopyright} 2010-2012 IEEE.",
keywords = "fault tolerance, masking, Privacy, smart metering, Electronic document identification systems, Energy resources, Fault tolerance, Masks, Speech intelligibility, Customer consumption data, Customer privacy, Data aggregation, Error resilience, Individual privacy, Privacy preserving, Smart metering, Spatio-temporal aggregation, Data privacy",
author = "F. Knirsch and G. Eibl and D. Engel",
note = "Cited By :57 Export Date: 14 December 2023 Funding text 1: ACKNOWLEDGMENT The financial support of the Josef Ressel Center by the Austrian Federal Ministry of Science, Research and Economy the Austrian National Foundation for Research, Technology and Development and Federal State of Salzburg are gratefully acknowledged. References: Eibl, G., Engel, D., Influence of data granularity on nonintru-sive appliance load monitoring (2014) Proc. 2nd ACM Workshop Inf. Hiding Multimedia Security (IH\&MMSec). Salzburg, Austria, pp. 147-151; Eibl, G., Engel, D., Influence of data granularity on smart meter privacy (2015) IEEE Trans. Smart Grid, 6 (2), pp. 930-939. , Mar; Finster, S., Baumgart, I., Privacy-aware smart metering: A survey (2014) IEEE Commun. Surveys Tuts., 16 (3), pp. 1732-1745. , 3rd Quart; Zhao, J., Jung, T., Wang, Y., Li, X., Achieving differential privacy of data disclosure in the smart grid (2014) Proc. IEEE INFOCOM IEEE Conf. Comput. 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year = "2018",
doi = "10.1109/TSG.2016.2630803",
language = "English",
volume = "9",
pages = "3351--3361",
journal = "IEEE Trans. Smart Grid",
issn = "1949-3053",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
number = "4",
}
SDG 7 Affordable and Clean Energy