A Framework For Privacy Diagnosis And Preservation In Data Publishing

Mirakabad, Mohammad Reza Zare (2010) A Framework For Privacy Diagnosis And Preservation In Data Publishing. PhD thesis, Universiti Sains Malaysia.

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Abstract

Privacy preservation in data publishing aims at the publication of data with protecting private information. Although removing direct identifier of individuals seems to protect their anonymity at first glance, private information may be revealed by joining the data to other external data. Privacy preservation addresses this privacy issue by introducing k-anonymity and l-diversity principles. Accordingly, privacy preservation techniques, namely k-anonymization and l-diversification algorithms, transform data (for example by generalization, suppression or fragmentation) to protect identity and sensitive information of individuals respectively.

Item Type:	Thesis (PhD)
Subjects:	Q Science > QA Mathematics > QA75.5-76.95 Electronic computers. Computer science
Divisions:	Pusat Pengajian Sains Komputer (School of Computer Sciences) > Thesis
Depositing User:	ASM Ab Shukor Mustapa
Date Deposited:	24 Sep 2018 07:55
Last Modified:	12 Apr 2019 05:26
URI:	http://eprints.usm.my/id/eprint/42061

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