Onto-DP: Constructing Neighborhoods for Differential Privacy on Ontological Databases

TL;DR

This paper introduces Onto-DP, an ontology-aware differential privacy extension that enhances privacy protection in ontological databases by considering semantic inference rules, addressing limitations of existing DP models.

Contribution

The paper proposes Onto-DP, a novel semantic-aware differential privacy framework that improves protection against inference attacks in ontological databases.

Findings

Naive DP models are insufficient against inference attacks.

Onto-DP effectively safeguards sensitive information in ontological databases.

Semantic awareness enhances differential privacy effectiveness.

Abstract

In this paper, we investigate how attackers can discover sensitive information embedded within databases by exploiting inference rules. We demonstrate the inadequacy of naively applied existing state of the art differential privacy (DP) models in safeguarding against such attacks. We introduce ontology aware differential privacy (Onto-DP), a novel extension of differential privacy paradigms built on top of any classical DP model by enriching it with semantic awareness. We show that this extension is a sufficient condition to adequately protect against attackers aware of inference rules.