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Wireless Personal Communications
Erschienen in: Wireless Personal Communications 3/2017

01.12.2016

An Improved Algorithm of Individuation K-Anonymity for Multiple Sensitive Attributes

verfasst von: Lin Zhang, Jie Xuan, Ruoqian Si, Ruchuan Wang

Erschienen in: Wireless Personal Communications | Ausgabe 3/2017

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Abstract

At present, most of privacy preserving approaches in data publishing are applied to single sensitive attribute. However, applying single-sensitive-attribute privacy preserving techniques directly into data with multiple sensitive attributes often causes leakage of large amount of private information. This paper focuses on the privacy preserving methods in data publishing for multiple sensitive attributes. It combines data anonymous methods based on lossy join with the idea of clustering. And it proposes an improved algorithm of individuation K-anonymity for multiple sensitive attributes—\( MSA(\alpha ,l) \) algorithm. By setting parameters \( \alpha \) and \( l \), it can restrain sensitive attribute values in equivalence class, to make a more balanced distribution of sensitive attributes and satisfy the demand of diversity, then this algorithm is applied to K-anonymity model. Finally, the result of experiment shows that this improved model can preserve the privacy of sensitive data, and it can also reduce the information hidden rate.
Vorheriger Artikel Wireless Sensor Network for Multi-channel 3D Data Synchronizing Acquisition System and Visual Simulation Research
Nächster Artikel Research on the Construction of the Universe Network Based on Quantum Entanglement Effect

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Metadaten
Titel
An Improved Algorithm of Individuation K-Anonymity for Multiple Sensitive Attributes
verfasst von
Lin Zhang
Jie Xuan
Ruoqian Si
Ruchuan Wang
Publikationsdatum
01.12.2016
Verlag
Springer US
Erschienen in
Wireless Personal Communications / Ausgabe 3/2017
Print ISSN: 0929-6212
Elektronische ISSN: 1572-834X
DOI
https://doi.org/10.1007/s11277-016-3922-4

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