保护隐私的数据发布

2010 IEEE 26th International Conference on Data Engineering Workshops (ICDEW 2010) Pub Date : 2010-03-01 DOI:10.1109/ICDEW.2010.5452722

Ruilin Liu, Wendy Hui Wang

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引用次数: 19

摘要

数据发布引起了人们对个人隐私的极大关注。最近的工作集中在不同的背景知识及其对已发布数据隐私的各种威胁上。然而，仍然存在一些类型的对手知识有待研究。在本文中，我通过使用全功能依赖关系(ffd)作为对手知识的一部分来解释我对隐私保护数据发布(PPDP)的研究。我也简要说明了我的研究计划。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Privacy-preserving data publishing

Data publishing has generated much concern on individual privacy. Recent work has focused on different background knowledge and their various threats to the privacy of published data. However, there still exist a few types of adversary knowledge waiting to be investigated. In this paper, I explain my research on privacy-preserving data publishing (PPDP) by using full functional dependencies (FFDs) as part of adversary knowledge. I also briefly explain my research plan.

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来源期刊

2010 IEEE 26th International Conference on Data Engineering Workshops (ICDEW 2010)

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