Privacy in "Anonymizing Horizontally Partitioned Data"

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Provided by: International Journal of Innovative Science Engineering and Technology (IJISET)
Topic: Data Management
Format: PDF
Privacy preserving data analysis and publishing has received considerable attention in recent years. Most work has been focused on a single data provider setting and considered the data recipient as an attacker. A limited background data is assumed from the literature of the attacker, and by considering specific types of attacks, the authors define privacy using relaxed adversarial notion. In this paper, malicious users are colluding the data and Anonymization techniques cannot control the all different attackers.
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