Distributed data anonymization

Fabio Martinelli, Mina Sheikhalishahi

Onderzoeksoutput: Hoofdstuk in Boek/Rapport/CongresprocedureConferentiebijdrageAcademicpeer review

2 Citaten (Scopus)

Samenvatting

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.

Originele taal-2Engels
TitelProceedings - 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
Plaats van productiePiscataway
UitgeverijInstitute of Electrical and Electronics Engineers
Pagina's580-586
Aantal pagina's7
ISBN van elektronische versie9781728130248
DOI's
StatusGepubliceerd - 8 aug 2019
Evenement17th 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
Duur: 5 aug 20198 aug 2019

Congres

Congres17th 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
Land/RegioJapan
StadFukuoka
Periode5/08/198/08/19

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