Efficient privacy-preserving data merging and skyline computation over multi-source encrypted data

Efficient privacy-preserving data merging and skyline computation over multi-source encrypted data
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多源加密数据的高效隐私保护数据合并和天际线计算

DOI:
10.1016/j.ins.2019.05.055
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发表时间:
2019-09
影响因子:
8.1
通讯作者:
Kim-Kwang Raymond Choo
Kim-Kwang Raymond Choo
中科院分区:
计算机科学1区
文献类型:
--
作者:
Y;ong Zheng;Rongxing Lu;Beibei Li;Jun Shao;Haomiao Yang;Kim-Kwang Raymond Choo

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从各种数据源定期收集的大量数据中进行有效的数据合并,对于发现相关和关键的感兴趣信息(例如,天际线)至关重要。然而,在数据合并和Skyline操作过程中存在隐私考虑,特别是在处理敏感数据(例如医疗保健数据)时。现有的数据融合和skyline计算方法要么没有充分考虑数据隐私,要么效率低下。因此,在本文中,我们的目标是解决多源加密数据的数据合并和天际线计算过程中的隐私和效率。具体地说,我们将左树与公钥加密和基于索引的天际线计算相结合,实现了加密数据的数据合并和天际线计算。首先,我们设计了一个非交互式的数据比较协议,使用公钥加密技术。这使我们能够在单个云服务器下比较加密和外包数据,而不是在以前的研究中使用两个非串通的云服务器。然后,将左树与公钥加密相结合,实现了高效率的隐私保护数据合并,即合并两棵大小为n1和n2的左树的计算复杂度为O(log2(n1 + n2)).第三,提出了一种基于索引和左树的天际线计算算法,可以有效地对合并后的加密数据进行天际线查询。然后,详细的安全性分析和性能评估表明,我们的方案是安全的,有效的数据合并和skyline计算。
Efficient data merging from the significant amount of data routinely collected from various data sources is crucial in the uncovering of relevant and key information of interest (eg, skyline). There are, however, privacy considerations during data merging and skyline operations, particularly when dealing with sensitive data (eg, healthcare data). Existing focuses on data merging and skyline computation either do not (fully) consider data privacy or have low efficiency. Thus, in this paper, we aim to address both privacy and efficiency during data merging and skyline computations over multi-source encrypted data. Specifically, we integrate the leftist tree with public key encryption and index based skyline computation to achieve data merging and skyline computation over encrypted data. First, we design a non-interactive data comparison protocol using public key encryption technique. This allows us to compare encrypted and outsourced data under a single cloud server instead of two non-colluding cloud servers in previous studies. Then, we combine the leftist tree with public key encryption to achieve privacy-preserving data merging with high efficiency, namely, O (log 2 (n 1+ n 2)) computational complexity for merging two leftist trees of sizes n 1 and n 2. Third, we present an index and leftist tree based skyline computation algorithm, which can efficiently perform skyline query over the merged encrypted data. Then, detailed security analysis and performance evaluation demonstrate that our scheme is both secure and efficient for data merging and skyline computation.
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