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Streaming, Plaintext Private Information Retrieval Using Regular Expressions on Arbitrary Length Search Strings

机译:流式传输,纯粹的私人信息使用正则表达式在任意长度搜索字符串上使用正则表达式检索

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Submitting a query to a plaintext stream can compromise search privacy, revealing the interests and motivations of the submitting party to the data owner. Current research in Private Information Retrieval (PIR) provides computationally private solutions based on partially-homomorphic encryption. These enable Alice to search Bob's data without revealing Alice's search criteria, sacrifice bandwidth (she doesn't have to tap the entire stream), or deploy a trusted device in Bob's domain. Building on two fixed-string retrieval techniques in [3] and [15], we developed a novel private pattern matching method that searches freeform, arbitrary length strings in streaming plaintext and retrieves corresponding elements. We present our design that encodes regular expressions into private queries, uses an obfuscation method to limit frequency and graph quotient attacks by Bob, and we provide experimental evidence to verify the feasibility of the approach. Our pattern matching technique extends the range of applications for plaintext PIR.
机译:向明文流提交查询可以危及搜索隐私,揭示提交方对数据所有者的兴趣和动机。私人信息的当前研究检索(PIR)基于部分均匀加密提供计算私有解决方案。这些使Alice能够在不显示Alice的搜索条件的情况下搜索Bob的数据,牺牲带宽(她不必点击整个流),或者在Bob域中部署可信设备。在[3]和[15]中,构建两个固定字符串检索技术,我们开发了一种新颖的私有模式匹配方法,在流媒体明文中搜索自由形式,任意长度字符串,并检索对应的元素。我们展示了我们的设计,将正则表达式编码为私人查询,使用混淆方法限制Bob的频率和图形商攻击,我们提供实验证据来验证方法的可行性。我们的模式匹配技术扩展了明文PIR的应用范围。

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