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

arXiv: https://arxiv.org/abs/2602.15614 · HTML: https://mlsanity.com/paper/2602.15614/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 17 Feb 2026.

## Built on by (most cited first, 1 of 1)

- [Inferring Sensitive Attributes from Knowledge Graph Embeddings: Attack and Defense Strategies](https://mlsanity.com/paper/2605.19644/) (2026)

## Abstract (arXiv)

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.