DP-Sync: Hiding Update Patterns in Secure Outsourced Databases with Differential Privacy
DP-Sync: Hiding Update Patterns in Secure Outsourced Databases with Differential Privacy
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DOI：
10.1145/3448016.3457306
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发表时间：
2021-03
期刊：
影响因子：
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通讯作者：
Chenghong Wang;Johes Bater;Kartik Nayak;Ashwin Machanavajjhala
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文献类型：
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作者：
Chenghong Wang;Johes Bater;Kartik Nayak;Ashwin Machanavajjhala
在本文中，我们认为隐私保护更新策略的安全外包增长数据库。这样的数据库允许在分析进行的同时对外包数据结构进行附加数据更新。尽管有大量的解决方案来安全地外包数据库计算，现有的技术不考虑通过更新模式可能泄露的信息。为了解决这个问题，我们设计了一个新的安全外包数据库框架，不断增长的数据，DP-Sync，它与一个大类现有的加密数据库进行互操作，并支持有效的更新，同时提供差异化的私人保证任何单一的更新。我们证明了DP-Sync的实际可行性的性能和准确性与广泛的经验评估真实的世界数据集。
In this paper, we consider privacy-preserving update strategies for secure outsourced growing databases. Such databases allow appendonly data updates on the outsourced data structure while analysis is ongoing. Despite a plethora of solutions to securely outsource database computation, existing techniques do not consider the information that can be leaked via update patterns. To address this problem, we design a novel secure outsourced database framework for growing data, DP-Sync, which interoperate with a large class of existing encrypted databases and supports efficient updates while providing differentially-private guarantees for any single update. We demonstrate DP-Sync's practical feasibility in terms of performance and accuracy with extensive empirical evaluations on real world datasets.