Differential Privacy for Relational Algebra: Improving the Sensitivity Bounds via Constraint Systems

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ID: 90007
2012
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Abstract
Differential privacy is a modern approach in privacy-preserving data analysis to control the amount of information that can be inferred about an individual by querying a database. The most common techniques are based on the introduction of probabilistic noise, often defined as a Laplacian parametric on the sensitivity of the query. In order to maximize the utility of the query, it is crucial to estimate the sensitivity as precisely as possible. In this paper we consider relational algebra, the classical language for queries in relational databases, and we propose a method for computing a bound on the sensitivity of queries in an intuitive and compositional way. We use constraint-based techniques to accumulate the information on the possible values for attributes provided by the various components of the query, thus making it possible to compute tight bounds on the sensitivity.
Reference Key
palamidessi2012differentialelectronic Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Palamidessi, Catuscia;Stronati, Marco;
Journal electronic proceedings in theoretical computer science
Year 2012
DOI
DOI not found
URL
http://arxiv.org/pdf/1207.0872v1
Keywords
Medicine Technology (General) Technology Science (General) Science mathematics electronic computers. computer science philosophy. psychology. religion

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