Distributed data anonymization

Fabio Martinelli, Mina Sheikhalishahi

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

2 Citations (Scopus)

Abstract

Data generalization is a widely-used privacy technique, in which an accurate value of sensitive information is replaced with a more general representation. The problem of data generalization becomes challenging when data is distributed among several agents, who are interested in releasing their table of data to shape a data mining algorithm on the whole of their data. The main issue originates from the fact that when each agent generalizes her own dataset locally, the released tables of data suffer from non-homogeneity. To sole the issue, all agents can generalize their data to the widest range of generalization. However, this approach causes utility loss. To optimally address this problem, in this study we present a framework that serves as a tool for data owners to generalize their data homogeneously before being published. The effectiveness of the proposed mechanism is validated through an experimental analysis on a benchmark dataset.

Original languageEnglish
Title of host publicationProceedings - IEEE 17th International Conference on Dependable, Autonomic and Secure Computing, IEEE 17th International Conference on Pervasive Intelligence and Computing, IEEE 5th International Conference on Cloud and Big Data Computing, 4th Cyber Science and Technology Congress, DASC-PiCom-CBDCom-CyberSciTech 2019
Place of PublicationPiscataway
PublisherInstitute of Electrical and Electronics Engineers
Pages580-586
Number of pages7
ISBN (Electronic)9781728130248
DOIs
Publication statusPublished - 8 Aug 2019
Event17th IEEE International Conference on Dependable, Autonomic and Secure Computing, IEEE 17th International Conference on Pervasive Intelligence and Computing, IEEE 5th International Conference on Cloud and Big Data Computing, 4th Cyber Science and Technology Congress, DASC-PiCom-CBDCom-CyberSciTech 2019 - Fukuoka, Japan
Duration: 5 Aug 20198 Aug 2019

Conference

Conference17th IEEE International Conference on Dependable, Autonomic and Secure Computing, IEEE 17th International Conference on Pervasive Intelligence and Computing, IEEE 5th International Conference on Cloud and Big Data Computing, 4th Cyber Science and Technology Congress, DASC-PiCom-CBDCom-CyberSciTech 2019
CountryJapan
CityFukuoka
Period5/08/198/08/19

Keywords

  • Distributed data analysis
  • Generalization
  • Privacy
  • Secure computation

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