Abstract
This chapter analyzes the possibility for an attacker to recover either individual measurements or probable individual measurements after the aggregations with any Privacy-Preserving Protocol (PPP). The relation between the measurements and the leak of privacy depends on several variables.
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References
J.-M. Bohli, C. Sorge, O. Ugus, A privacy model for smart metering, in 2010 IEEE International Conference on Communications Workshops (ICC) (2010), pp. 1–5. doi:10.1109/ICCW.2010.5503916
C. Dwork, Differential privacy: a survey of results. English, in Theory and Applications of Models of Computation, ed. by M. Agrawal et al., vol. 4978. Lecture Notes in Computer Science (Springer, Berlin, Heidelberg, 2008), pp. 1–19. isbn:978-3-540-79227-7. doi:10.1007/978-3-540-79228-4_1. http://dx.doi.org/10.1007/978-3-540-79228-4_1
G. Eibl, D. Engel, Influence of data granularity on smart meter privacy. IEEE Trans. Smart Grid 6 (2), 930–939 (2015). issn:1949–3053. doi:10.1109/TSG.2014.2376613
U. Greveler, B. Justus, D. Löhr, Multimedia content identification through smart meter power usage profiles, in Computers, Privacy and Data Protection (CPDP 2012). The Steering Committee of The World Congress in Computer Science, Computer Engineering and Applied Computing (WorldComp) (2012)
M. Jawurek, F. Kerschbaum, Fault-tolerant privacy- preserving statistics, in Privacy Enhancing Technologies, ed. by S. Fischer-Hübner, M. Wright, vol. 7384. Lecture Notes in Computer Science (Springer, Berlin, Heidelberg, 2012), pp. 221–238. isbn:978-3-642-31679-1. doi:10.1007/978-3-642-31680-7_12. http://dx.doi.org/10.1007/978-3-642-31680-7_12
A. Molina-Markham et al., Private memoirs of a smart meter, in Proceedings of the 2nd ACM Workshop on Embedded Sensing Systems for Energy-Efficiency in Building. BuildSys ’10 (ACM, Zurich, 2010), pp. 61–66. isbn:978-1-4503-0458-0. doi:10.1145/1878431.1878446. http://doi.acm.org/10.1145/1878431.1878446
M. Savi, C. Rottondi, G. Verticale, Evaluation of the precision-privacy tradeoff of data perturbation for smart metering. IEEE Trans. Smart Grid 6 (5), 2409–2416 (2015). issn:1949-3053. doi:10.1109/TSG.2014.2387848
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Borges de Oliveira, F. (2017). Quantifying the Aggregation Size. In: On Privacy-Preserving Protocols for Smart Metering Systems. Springer, Cham. https://doi.org/10.1007/978-3-319-40718-0_5
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DOI: https://doi.org/10.1007/978-3-319-40718-0_5
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