A Novel Fuzzy Search Approach over Encrypted Data with Improved Accuracy and Efficiency
A Novel Fuzzy Search Approach over Encrypted Data with Improved Accuracy and Efficiency
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发表时间：
2019-04
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通讯作者：
Jinkun Cao;Jinhao Zhu;Liwei Lin;Zhengui Xue;Ruhui Ma;Haibing Guan
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作者：
Jinkun Cao;Jinhao Zhu;Liwei Lin;Zhengui Xue;Ruhui Ma;Haibing Guan
近年来，随着云计算的普及，越来越多的企业和个人将他们的数据外包给云服务器。为了避免隐私泄露，外包数据通常在发送到云服务器之前进行加密，这使得传统的纯文本搜索方案无法使用。为了兼顾安全性和可搜索性，提出了搜索支持的加密算法。然而，当查询请求中存在打字错误和语义多样性时，许多以前的方案都存在严重的漏洞。为了克服这些缺陷，搜索支持的加密设计总是期望有更高的容错性，有时被定义为‘模糊搜索’。本文提出了一种新的加密和外包数据多关键字模糊搜索方案。我们的方法引入了一种新的机制来将自然语言表达映射到单词向量空间。与以前的方法相比，我们的设计在涉及多种类型的打字错误时表现出更高的稳健性。此外，我们的方法还通过新颖的数据结构进行了改进，以提高搜索效率。这两项创新在准确性和效率方面都可以很好地发挥作用。此外，这些设计不会损害基本安全。在真实数据集上的实验证明了我们提出的方法的有效性，该方法的性能优于目前流行的专注于类似任务的方法。
As cloud computing becomes prevalent in recent years, more and more enterprises and individuals outsource their data to cloud servers. To avoid privacy leaks, outsourced data usually is encrypted before being sent to cloud servers, which disables traditional search schemes for plain text. To meet both end of security and searchability, search-supported encryption is proposed. However, many previous schemes suffer severe vulnerability when typos and semantic diversity exist in query requests. To overcome such flaw, higher error-tolerance is always expected for search-supported encryption design, sometimes defined as 'fuzzy search'. In this paper, we propose a new scheme of multi-keyword fuzzy search over encrypted and outsourced data. Our approach introduces a new mechanism to map a natural language expression into a word-vector space. Compared with previous approaches, our design shows higher robustness when multiple kinds of typos are involved. Besides, our approach is enhanced with novel data structures to improve search efficiency. These two innovations can work well for both accuracy and efficiency. Moreover, these designs will not hurt the fundamental security. Experiments on a real-world dataset demonstrate the effectiveness of our proposed approach, which outperforms currently popular approaches focusing on similar tasks.