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EDBT
2010
ACM

Algorithm-safe privacy-preserving data publishing

11 years 3 months ago
Algorithm-safe privacy-preserving data publishing
This paper develops toolsets for eliminating algorithm-based disclosure from existing privacy-preserving data publishing algorithms. We first show that the space of algorithm-based disclosure is larger than previously believed and thus more prevalent and dangerous. Then, we formally define Algorithm-Safe Publishing (ASP) to model the threats from algorithm-based disclosure. To eliminate algorithmbased disclosure from existing data publishing algorithms, we propose two generic tools for revising their design: worst-case eligibility test and stratified pick-up. We demonstrate the effectiveness of our tools by using them to transform two popular existing diversity algorithms, Mondrian 1 and Hilb, to SP-Mondrian and SPHilb which are algorithm-safe. We conduct extensive experiments to demonstrate the effectiveness of SP-Mondrian and SP-Hilb in terms of data utility and efficiency.
Xin Jin, Nan Zhang 0004, Gautam Das
Added 02 Sep 2010
Updated 02 Sep 2010
Type Conference
Year 2010
Where EDBT
Authors Xin Jin, Nan Zhang 0004, Gautam Das
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