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Privacy Analysis with a Distributed Transition System and a Data-Wise Metric

Abstract : We introduce a logical framework DLTTS (Distributed Labeled Tagged Transition System), built using concepts from Proba- bilistic Automata, Probabilistic Concurrent Systems, and Probabilistic labelled transition systems. We show that DLTTS can be used to formally model how a given piece of private information P (e.g. a tuple) stored in a given database D protected by generalization and/or noise addition mechanisms, can get captured progressively by an agent repeat- edly querying D, by using additional non-private data, as well as knowl- edge deducible with a more general notion of adjacency based on metrics defined ‘value-wise’; such metrics also play a role in differentially private protection mechanisms.
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Conference papers
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https://hal.archives-ouvertes.fr/hal-03767722
Contributor : Siva Anantharaman Connect in order to contact the contributor
Submitted on : Friday, September 2, 2022 - 10:59:16 AM
Last modification on : Sunday, September 18, 2022 - 9:06:30 PM

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  • HAL Id : hal-03767722, version 1

Citation

Siva Anantharaman, Sabine Frittella, Benjamin Nguyen. Privacy Analysis with a Distributed Transition System and a Data-Wise Metric. Privacy in Statistical Databases (PSD), Sep 2022, PARIS, France. pp.15--30. ⟨hal-03767722⟩

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