Enabling Personalized Search over Encrypted Outsourced Data with Efficiency Improvement
Enabling Personalized Search over Encrypted Outsourced Data with Efficiency Improvement
复制标题
实现对加密外包数据的个性化搜索并提高效率
DOI：
10.1109/tpds.2015.2506573
复制
发表时间：
2016-09-01
影响因子：
5.3
通讯作者：
Huang, Fengxiao
中科院分区：
文献类型：
--
作者：
Fu, Zhangjie;Ren, Kui;Huang, Fengxiao
在云计算环境下，基于外包数据的可搜索加密方案是一个研究热点.然而，现有的外包云数据加密搜索大多遵循“一刀切”的模式，忽略了个性化的搜索意图。而且，它们大多只支持精确的关键字搜索，这极大地影响了数据可用性和用户体验。因此如何设计一个可搜索的加密方案，支持个性化搜索，提高用户搜索体验仍然是一个非常具有挑战性的任务。在本文中，我们首次研究和解决的问题，个性化的多关键字排名搜索加密数据（PRSE），同时保护隐私的云计算。在语义本体WordNet的帮助下，通过分析用户的搜索历史，建立了单个用户的用户兴趣模型，并采用评分机制来智能地表达用户兴趣。为了解决“一刀切”和关键字精确搜索模型的局限性，我们提出了两个PRSE计划不同的搜索意图。在真实数据集上的大量实验验证了我们的分析，并表明我们提出的解决方案是非常有效的。
In cloud computing, searchable encryption scheme over outsourced data is a hot research field. However, most existing works on encrypted search over outsourced cloud data follow the model of "one size fits all" and ignore personalized search intention. Moreover, most of them support only exact keyword search, which greatly affects data usability and user experience. So how to design a searchable encryption scheme that supports personalized search and improves user search experience remains a very challenging task. In this paper, for the first time, we study and solve the problem of personalized multi-keyword ranked search over encrypted data (PRSE) while preserving privacy in cloud computing. With the help of semantic ontologyWordNet, we build a user interest model for individual user by analyzing the user's search history, and adopt a scoring mechanism to express user interest smartly. To address the limitations of the model of "one size fit all" and keyword exact search, we propose two PRSE schemes for different search intentions. Extensive experiments on real-world dataset validate our analysis and show that our proposed solution is very efficient and effective.