MET??P: revisiting Privacy-Preserving Data Publishing using secure devices
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 Met ??P, 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.
privacy-preserving data publishing secure device sanitization anonymization privacy