KR2024Proceedings of the 21st International Conference on Principles of Knowledge Representation and ReasoningProceedings of the 21st International Conference on Principles of Knowledge Representation and Reasoning

Hanoi, Vietnam. November 2-8, 2024.

Edited by
  1. Pierre Marquis,
  2. Magdalena Ortiz
  3. Maurice Pagnucco

ISSN: 2334-1033
ISBN: 978-1-956792-05-8

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Published by

Copyright © 2024 International Joint Conferences on Artificial Intelligence Organization

Lost in the Crowd: k-unmatchability in Anonymized Knowledge Graphs

  1. Piero Andrea Bonatti(University of Naples Federico II)
  2. Francesco Magliocca(University of Naples Federico II)
  3. Luigi Sauro(University of Naples Federico II)
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BibTeX
https://doi.org/10.24963/kr.2024/18

Keywords

  1. Reasoning in knowledge graphs-General
  2. Semantic web-General

Abstract

This paper introduces and investigates k-unmatchability, a counterpart of k-anonymity for knowledge graphs.

Like k-anonimity, k-unmatchability enhances privacy by ensuring that any individual in any external source can always be matched to either none or at least k different anonymized individuals.

The tradeoff between privacy protection and information loss can be controlled with parameter k.

We analyze the data complexity of k-unmatchability under different notions of anonymization.