Efficient privacy-preserved data query over ciphertext in cloud computing

Efficient privacy-preserved data query over ciphertext in cloud computing
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云计算中基于密文的高效隐私保护数据查询

DOI:
10.1002/sec.824
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发表时间:
2014-06
影响因子:
--
通讯作者:
Cui Yihui
Cui Yihui
中科院分区:
计算机科学4区
文献类型:
--
作者:
Song Wei;Peng Zhiyong;Wang Qian;Cheng Fangquan;Wu Xiaoxin;Cui Yihui

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随着云计算的普及,越来越多的敏感信息被集中到云端。解决云数据隐私问题的一个基本方法是在外包之前对数据进行加密。然而,这使得有效的数据利用(例如搜索)成为一项非常具有挑战性的任务。尽管已经提出了一些可搜索加密方案来允许用户搜索加密数据,但是这些技术极其难以提供具有各种服务模式(例如非均匀数据分布、非均匀查询工作量和属性连接查询)的有效加密数据查询。在本文中,我们研究了在云计算中查询密文数字关系数据的有效的隐私保护数据查询方法。为了像 DBMS 通过 SQL 一样提供高效的关系数据查询服务,我们提出了一种面向服务的查询 SOQ 算法,该算法根据敏感数据分布和查询工作量自适应调整加密数据桶。此外,我们提出了一个两阶段索引来解决加密属性之间的连接查询问题,据我们所知,该问题尚未得到很好的解决。我们设计了实验来评估我们的方案和算法的性能,结果表明我们的方法实现了令人满意的加密数据查询性能。版权所有 © 2013 约翰·威利父子有限公司
As cloud computing becomes prevalent, more and more sensitive information are being centralized into the cloud. A basic methodology that may address cloud data privacy issue is to encrypt the data before outsourcing. However, this makes effective data utilization, for example, searching a very challenging task. Although some searchable encryption schemes have been proposed to allow a user to search over encrypted data, these techniques are extremely difficult to provide efficient encrypted data query with various service patterns such as nonuniform data distribution, nonuniform query workload, and attributes join query. In this paper, we research efficient privacy-preserved data query methodologies for querying cipher-text numeric relational data in cloud computing. To provide efficient relational data query service just as DBMS does through SQL, we propose a service-oriented query SOQ algorithm that adaptively adjusts the encrypted data buckets based on sensitive data distribution and query workload. Moreover, we propose a two-stage index to address the issue of join query between encrypted attributes that has not been well solved to our knowledge. We design experiments to evaluate performances of our schemes and algorithms, which show that our methods achieve satisfactory encrypted data query performances. Copyright © 2013 John Wiley & Sons, Ltd.
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