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A Survey on Privacy Preserving Dynamic Data Publishing
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Author(s): Salheddine Kabou (LabRI Laboratory, Ecole Superieure en Informatique, Sidi Bel-Abbes, Algeria), Sidi mohamed Benslimane (LabRI Laboratory, Ecole Superieure en Informatique, Sidi Bel-Abbes, Algeria)and Mhammed Mosteghanemi (Ecole Nationale Supérieure d'Informatique, Bab Ezzouar, Algeria)
Copyright: 2021
Pages: 23
Source title:
Research Anthology on Privatizing and Securing Data
Source Author(s)/Editor(s): Information Resources Management Association (USA)
DOI: 10.4018/978-1-7998-8954-0.ch079
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Abstract
Many organizations, especially small and medium business (SMB) enterprises require the collection and sharing of data containing personal information. The privacy of this data must be preserved before outsourcing to the commercial public. Privacy preserving data publishing PPDP refers to the process of publishing useful information while preserving data privacy. A variety of approaches have been proposed to ensure privacy by applying traditional anonymization models which focused only on the single publication of datasets. In practical applications, data publishing is more complicated where the organizations publish multiple times for different recipients or after modifications to provide up-to-date data. Privacy preserving dynamic data publication PPDDP is a new process in privacy preservation which addresses the anonymization of the data for different purposes. In this survey, the author will systematically evaluate and summarize different studies to PPDDP, clarify the differences and requirements between the scenarios that can exist, and propose future research directions.
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