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arXiv 1702.08342cs.CRcs.PL
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Curie:基于策略的安全数据交换

Curie: Policy-based Secure Data Exchange

Z. Berkay Celik, Hidayet Aksu, Abbas Acar, Ryan Sheatsley, A. Selcuk Uluagac, Patrick McDaniel

摘要:

合作伙伴--用户、组织、公司--之间的数据共享对于许多领域的数据分析的发展至关重要。通过安全计算和差分隐私共享,这些合作伙伴可以以受控的方式对其敏感数据执行私有计算。然而,在现实中,成员之间存在着复杂的关系。政治、法规、利益、信任、数据要求和需求是众多原因之一。因此,需要一种机制来满足关于数据共享的这些冲突关系。本文介绍了居里,一种方法来交换成员之间的数据,其成员具有复杂的关系。CPL的政策语言,允许成员定义的数据交换要求的规格介绍。成员(合作伙伴)通过他们的本地政策来确定谁和什么可以交换,并协商一个全球共享协议。该协议在多方计算中实现,以保证成员之间的共享符合协商的策略。居里夫人的使用是通过一个例子,最近推出的安全多方计算和差分隐私框架,并探讨政策和性能权衡的医疗保健应用程序进行验证。

英文摘要:

Data sharing among partners---users, organizations, companies---is crucial for the advancement of data analytics in many domains. Sharing through secure computation and differential privacy allows these partners to perform private computations on their sensitive data in controlled ways. However, in reality, there exist complex relationships among members. Politics, regulations, interest, trust, data demands and needs are one of the many reasons. Thus, there is a need for a mechanism to meet these conflicting relationships on data sharing. This paper presents Curie, an approach to exchange data among members whose membership has complex relationships. The CPL policy language that allows members to define the specifications of data exchange requirements is introduced. Members (partners) assert who and what to exchange through their local policies and negotiate a global sharing agreement. The agreement is implemented in a multi-party computation that guarantees sharing among members will comply with the policy as negotiated. The use of Curie is validated through an example of a health care application built on recently introduced secure multi-party computation and differential privacy frameworks, and policy and performance trade-offs are explored.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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