Full Citation

Title: METAP: revisiting Privacy-Preserving Data Publishing using secure devices

Citation Type: Journal Article

Publication Year: 2014

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Abstract: The goal of Privacy-Preserving Data Publishing (PPDP) is to generate a sanitized (i.e. harmless) view of sensitive personal data (e.g. a health survey), to be released to some agencies or simply the public. However, traditional PPDP practices all make the assumption that the process is run on a trusted central server. In this article, we argue that the trust assumption on the central server is far too strong. We propose METAP, a generic fully distributed protocol, to execute various forms of PPDP algorithms on an asymmetric architecture composed of low power secure devices and a powerful but untrusted infrastructure. We show that this protocol is both correct and secure against honest-but-curious or malicious adversaries. Finally, we provide an experimental validation showing that this protocol can support PPDP processes scaling up to nation-wide surveys.

Url: http://link.springer.com/article/10.1007%2Fs10619-013-7122-x

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Authors: Pucheral, Philippe; Nguyen, Benjamin; Allard, Tristan

Periodical (Full): Distributed and Parallel Databases

Issue: 2

Volume: 32

Pages: 191-245

Data Collections: IPUMS USA

Topics: Methodology and Data Collection

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