AuthPDB: Authentication of Probabilistic Queries on Outsourced Uncertain Data

Bo Zhang, Boxiang Dong, Haipei Sun, Wendy Hui Wang
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引用次数: 1

Abstract

Query processing over uncertain data has gained much attention recently. Due to the high computational complexity of query evaluation on uncertain data, the data owner can outsource her data to a server that provides query evaluation as a service. However, a dishonest server may return cheap (and incorrect) query answers, hoping that the client who has weak computational power cannot catch the incorrect results. To address the integrity issue, in this paper, we design AuthPDB, a framework that supports efficient authentication of query evaluation for both all-answer and top-k queries on outsourced probabilistic databases. Our empirical results on real-world datasets demonstrate the effectiveness and efficiency of AuthPDB.
AuthPDB:外包不确定数据的概率查询认证
不确定数据的查询处理近年来受到了广泛的关注。由于对不确定数据进行查询评估的计算复杂度很高,数据所有者可以将其数据外包给提供查询评估服务的服务器。然而,不诚实的服务器可能会返回廉价(和不正确)的查询答案,希望计算能力较弱的客户端无法捕获错误的结果。为了解决完整性问题,在本文中,我们设计了AuthPDB框架,该框架支持对外包概率数据库上的所有答案和top-k查询进行有效的查询评估认证。我们在真实数据集上的实证结果证明了AuthPDB的有效性和效率。
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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