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Partitioned Data Security on Outsourced Sensitive and Non-Sensitive Data

机译:外包敏感和非敏感数据的分区数据安全性

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Despite extensive research on cryptography, secure and efficient query processing over outsourced data remains an open challenge. This paper continues along the emerging trend in secure data processing that recognizes that the entire dataset may not be sensitive, and hence, non-sensitivity of data can be exploited to overcome limitations of existing encryption-based approaches. We propose a new secure approach, entitled query binning (QB) that allows non-sensitive parts of the data to be outsourced in clear-text while guaranteeing that no information is leaked by the joint processing of non-sensitive data (in clear-text) and sensitive data (in encrypted form). QB maps a query to a set of queries over the sensitive and non-sensitive data in a way that no leakage will occur due to the joint processing over sensitive and non-sensitive data. Interestingly, in addition to improve performance, we show that QB actually strengthens the security of the underlying cryptographic technique by preventing size, frequency-count, and workload-skew attacks.
机译:尽管对密码学进行了广泛的研究,但是对外包数据进行安全有效的查询处理仍然是一个开放的挑战。本文沿着安全数据处理的新兴趋势继续发展,该趋势认识到整个数据集可能并不敏感,因此,可以利用数据的非敏感性来克服现有基于加密方法的局限性。我们提出了一种名为“查询分箱(QB)”的新安全方法,该方法允许将数据的非敏感部分以明文形式外包,同时保证通过非敏感数据的联合处理(明文形式)不会泄漏任何信息。 )和敏感数据(以加密形式)。 QB将查询映射到敏感和非敏感数据上的一组查询,这样就不会由于对敏感和非敏感数据的联合处理而发生泄漏。有趣的是,除了提高性能之外,我们还证明了QB通过防止大小,频率计数和工作负载偏斜攻击实际上增强了基础密码技术的安全性。

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