An Efficient Privacy-Preserving Ranked Keyword Search Method
An Efficient Privacy-Preserving Ranked Keyword Search Method
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DOI：
10.1109/tpds.2015.2425407
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发表时间：
2016-04
影响因子：
5.3
通讯作者：
Chi Chen;Xiaojie Zhu;Peisong Shen;Jiankun Hu;Song Guo;Z. Tari;Albert Y. Zomaya
中科院分区：
文献类型：
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作者：
Chi Chen;Xiaojie Zhu;Peisong Shen;Jiankun Hu;Song Guo;Z. Tari;Albert Y. Zomaya
为了保护隐私，云数据所有者更喜欢以加密形式外包文档。因此，开发高效、可靠的密文搜索技术是十分必要的。一个挑战是，文档之间的关系通常会在加密过程中被隐藏，这将导致搜索精度性能的显著下降。此外，数据中心的数据量也经历了急剧增长。这使得设计能够对大量加密数据提供高效、可靠的在线信息检索的密文搜索方案变得更加具有挑战性。为了支持更多的搜索语义，同时满足大数据环境下对密文快速搜索的需求，本文提出了一种分层聚类方法。提出的分层方法基于最小相关阈值对文档进行聚类，然后将结果聚类划分为子聚类，直到达到对最大聚类大小的约束。在搜索阶段，这种方法可以达到线性计算复杂度，而不是文档集合的指数级增长。为了验证搜索结果的真实性，本文设计了一种最小哈希子树结构。实验是使用IEEE explorer建立的集合集进行的。结果表明，随着数据集中文档数量的急剧增加，本文方法的搜索时间呈线性增长，而传统方法的搜索时间呈指数增长。此外，该方法在检索文档的等级隐私性和相关性方面优于传统方法。
Cloud data owners prefer to outsource documents in an encrypted form for the purpose of privacy preserving. Therefore it is essential to develop efficient and reliable ciphertext search techniques. One challenge is that the relationship between documents will be normally concealed in the process of encryption, which will lead to significant search accuracy performance degradation. Also the volume of data in data centers has experienced a dramatic growth. This will make it even more challenging to design ciphertext search schemes that can provide efficient and reliable online information retrieval on large volume of encrypted data. In this paper, a hierarchical clustering method is proposed to support more search semantics and also to meet the demand for fast ciphertext search within a big data environment. The proposed hierarchical approach clusters the documents based on the minimum relevance threshold, and then partitions the resulting clusters into sub-clusters until the constraint on the maximum size of cluster is reached. In the search phase, this approach can reach a linear computational complexity against an exponential size increase of document collection. In order to verify the authenticity of search results, a structure called minimum hash sub-tree is designed in this paper. Experiments have been conducted using the collection set built from the IEEE Xplore. The results show that with a sharp increase of documents in the dataset the search time of the proposed method increases linearly whereas the search time of the traditional method increases exponentially. Furthermore, the proposed method has an advantage over the traditional method in the rank privacy and relevance of retrieved documents.