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DOI: 10.5445/IR/1000043576

Deploying and Evaluating Pufferfish Privacy for Smart Meter Data (Technical Report)

Kessler, Stephan; Buchmann, Erik; Böhm, Klemens

Abstract:
Information hiding ensures privacy by transforming personalized data so that certain sensitive information cannot be inferred any more. One state-of-the-art information-hiding approach is the Pufferfish framework. It lets the users specify their privacy requirements as so-called discriminative pairs of secrets, and it perturbs data so that an adversary does not learn about the probability distribution of such pairs. However, deploying the framework on complex data such as time series requires application specific work. This includes a general definition of the representation of secrets in the data. Another issue is that the tradeoff between Pufferfish privacy and utility of the data is largely unexplored in quantitative terms. In this study, we quantify this tradeoff for smart meter data. Such data contains fine-grained time series of power-consumption data from private households. Disseminating such data in an uncontrolled way puts privacy at risk. We investigate how time series of energy consumption data must be transformed to facilitate specifying secrets that Pufferfish can use. We ensure the generality of our study by looking a ... mehr


Zugehörige Institution(en) am KIT Institut für Programmstrukturen und Datenorganisation (IPD)
Publikationstyp Forschungsbericht
Jahr 2014
Sprache Englisch
Identifikator ISSN: 2190-4782
URN: urn:nbn:de:swb:90-435765
KITopen ID: 1000043576
Verlag Karlsruhe
Serie Karlsruhe Reports in Informatics ; 2014,13
URLs Version 2015
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