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