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本文引用的文献

1
Class Restricted Clustering and Micro-Perturbation for Data Privacy.用于数据隐私的类别受限聚类与微扰动
Manage Sci. 2013 Apr 1;59(4). doi: 10.1287/mnsc.1120.1584.

在保护隐私的前提下定价和传播客户数据。

Pricing and disseminating customer data with privacy awareness.

作者信息

Li Xiao-Bai, Raghunathan Srinivasan

机构信息

Department of Operations & Information Systems, University of Massachusetts Lowell, United States.

School of Management, University of Texas at Dallas, United States.

出版信息

Decis Support Syst. 2014 Mar 1;59:63-73. doi: 10.1016/j.dss.2013.10.006.

DOI:10.1016/j.dss.2013.10.006
PMID:24839337
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC4019429/
Abstract

Organizations today regularly share their customer data with their partners to gain competitive advantages. They are also often requested or even required by a third party to provide customer data that are deemed sensitive. In these circumstances, organizations are obligated to protect the privacy of the individuals involved while still benefiting from sharing data or meeting the requirement for releasing data. In this study, we analyze the tradeoff between privacy and data utility from the perspective of the data owner. We develop an incentive-compatible mechanism for the data owner to price and disseminate private data. With this mechanism, a data user is motivated to reveal his true purpose of data usage and acquire the data that suits to that purpose. Existing economic studies of information privacy primarily consider the interplay between the data owner and the individuals, focusing on problems that occur in the of private data. This study, however, examines the privacy issue facing a data owner organization in the of private data to a third party data user when the real purpose of data usage is unclear and the released data could be misused.

摘要

如今,组织经常与合作伙伴共享客户数据以获取竞争优势。他们还经常被第三方要求甚至强制提供被视为敏感的客户数据。在这种情况下,组织有义务保护相关个人的隐私,同时仍能从数据共享中受益或满足数据发布要求。在本研究中,我们从数据所有者的角度分析隐私与数据效用之间的权衡。我们为数据所有者开发了一种激励兼容机制,用于对私有数据定价和传播。通过这种机制,数据使用者有动力揭示其数据使用的真实目的,并获取适合该目的的数据。现有的信息隐私经济研究主要考虑数据所有者与个人之间的相互作用,关注私有数据泄露过程中出现的问题。然而,本研究考察的是当数据使用的真实目的不明且所发布的数据可能被滥用时,数据所有者组织在向第三方数据使用者泄露私有数据的情况下所面临的隐私问题。