Efficient privacy-aware search over encrypted databases

Mehmet Kuzu, M. S. Islam, Murat Kantarcioglu
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引用次数: 13

Abstract

In recent years, database as a service (DAS) model where data management is outsourced to cloud service providers has become more prevalent. Although DAS model offers lower cost and flexibility, it necessitates the transfer of potentially sensitive data to untrusted cloud servers. To ensure the confidentiality, encryption of sensitive data before its transfer to the cloud emerges as an important option. Encrypted storage provides protection but it complicates data processing including crucial selective record retrieval. To achieve selective retrieval over encrypted collection, considerable amount of searchable encryption schemes have been proposed in the literature with distinct privacy guarantees. Among the available approaches, oblivious RAM based ones offer optimal privacy. However, they are computationally intensive and do not scale well to very large databases. On the other hand, almost all efficient schemes leak some information, especially data access pattern to the remote servers. Unfortunately, recent evidence on access pattern leakage indicates that adversary's background knowledge could be used to infer the contents of the encrypted data and may potentially endanger individual privacy. In this paper, we introduce a novel construction for practical and privacy-aware selective record retrieval over encrypted databases. Our approach leaks obfuscated access pattern to enable efficient retrieval while ensuring individual privacy. Applied obfuscation is based on differential privacy which provides rigorous individual privacy guarantees against adversaries with arbitrary background knowledge.
在加密数据库上进行高效的隐私感知搜索
近年来,将数据管理外包给云服务提供商的数据库即服务(DAS)模型变得越来越普遍。尽管DAS模型提供了较低的成本和灵活性,但它需要将潜在的敏感数据传输到不受信任的云服务器。为了确保机密性,在将敏感数据传输到云之前对其进行加密成为一个重要的选择。加密存储提供了保护,但它使数据处理变得复杂,包括关键的选择性记录检索。为了实现对加密集合的选择性检索,文献中提出了大量具有不同隐私保证的可搜索加密方案。在可用的方法中,基于遗忘内存的方法提供了最佳的隐私。然而,它们是计算密集型的,不能很好地扩展到非常大的数据库。另一方面,几乎所有的高效方案都会向远程服务器泄漏一些信息,尤其是数据访问模式。不幸的是,最近关于访问模式泄露的证据表明,攻击者的背景知识可能被用来推断加密数据的内容,并可能危及个人隐私。在本文中,我们介绍了一种实用且具有隐私意识的加密数据库选择性记录检索的新结构。我们的方法泄漏了混淆的访问模式,在确保个人隐私的同时实现了有效的检索。应用混淆基于差分隐私,它为具有任意背景知识的对手提供严格的个人隐私保证。
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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