# Reasoning about disclosure in data integration in the presence of source constraints

## TL;DR

This paper investigates how source constraints influence privacy disclosure analysis in data integration systems, providing bounds on what an attacker can infer considering source semantics and constraints.

## Contribution

It introduces a formal framework for analyzing disclosure in data integration with source constraints, highlighting their significant impact on privacy assessments.

## Key findings

- Source constraints significantly affect disclosure analysis.
- The paper establishes bounds on source-aware disclosure.
- Constraints can either limit or enable information disclosure.

## Abstract

Data integration systems allow users to access data sitting in multiple sources by means of queries over a global schema, related to the sources via mappings. Data sources often contain sensitive information, and thus an analysis is needed to verify that a schema satisfies a privacy policy, given as a set of queries whose answers should not be accessible to users. Such an analysis should take into account not only knowledge that an attacker may have about the mappings, but also what they may know about the semantics of the sources. In this paper, we show that source constraints can have a dramatic impact on disclosure analysis. We study the problem of determining whether a given data integration system discloses a source query to an attacker in the presence of constraints, providing both lower and upper bounds on source-aware disclosure analysis.