Privacy-Preserving Techniques and System for Streaming Databases

Anderson Santana de Oliveira, F. Kerschbaum, Hoonwei Lim, Su-Yang Yu
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引用次数: 3

Abstract

Streaming databases and other distributed, event-based systems are very useful tools for business and security applications. When event sources and event processing are distributed across multiple distinct domains, confidentiality and privacy issues emerge. These can be addressed by a number of cryptographic techniques. In this paper we consider high-performance symmetric encryption techniques. We build a system for privacy-preserving event correlation and evaluate the performance of the its techniques. We demonstrate efficient privacy-preserving event correlation using equality tests, greater-than comparisons and range queries. The results indicate that in comparable settings, it is therefore recommended to employ these techniques to address pertinent security and privacy concerns.
流数据库的隐私保护技术与系统
流数据库和其他基于事件的分布式系统对于业务和安全应用程序来说是非常有用的工具。当事件源和事件处理分布在多个不同的域时,就会出现机密性和隐私问题。这些可以通过许多加密技术来解决。在本文中,我们考虑高性能对称加密技术。我们建立了一个隐私保护事件关联系统,并评估了其技术的性能。我们使用相等性测试、大于比较和范围查询证明了有效的保护隐私的事件关联。结果表明,在类似的设置中,因此建议采用这些技术来解决相关的安全和隐私问题。
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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