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Privacy Preserving synonym based fuzzy multi-keyword ranked search over encrypted cloud data

机译:在加密的云数据上基于隐私保护同义词的模糊多关键字排名搜索

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Cloud Storage is currently one of the most widely used applications of cloud. As usage of cloud is increasing, critical and personal data is also being outsourced making it important to maintain confidentiality and integrity of this data. A basic way of protecting data is encrypting it before outsourcing, but the retrieval of required files from the encrypted cloud becomes a problem which requires searching over the encrypted data. Various schemes have been proposed to deal with this issue of searching over encrypted cloud data, however none of the existent schemes provide optimum user search experience resembling plaintext search. In this paper we propose Privacy Preserving Synonym Based Fuzzy Multi-Keyword Ranked Search Over Encrypted Cloud Data, a scheme which enhances user search experience to a paramount by providing both fuzzy and synonym based multi-keyword ranked search, thereby taking encrypted search experience closer to free text search engines. The scheme additionally improves upon index generation time and search time in comparison to existing schemes by utilizing a binary tree based dynamic index. Experimental results portray the effectiveness of this proposed scheme as it reduces the search time, i.e. the time for finding the desired documents, by 90% along with minimizing overhead of updating index when new files need to be uploaded (index generation time) as compared to the existing efficient indexing schemes in literature for a similar dataset. Optimization of search time together with index generation time has not been achieved to this extent before.
机译:云存储是当前使用最广泛的云应用程序之一。随着云使用量的增加,关键数据和个人数据也已外包,这对于保持此数据的机密性和完整性非常重要。保护数据的一种基本方法是在外包之前对其进行加密,但是从加密的云中检索所需文件成为一个问题,需要搜索加密的数据。已经提出了各种方案来解决在加密的云数据上进行搜索的问题,但是,没有一种方案可以提供类似于明文搜索的最佳用户搜索体验。在本文中,我们提出了在加密云数据上基于隐私保护的基于同义词的模糊多关键字排名搜索,该方案通过提供基于模糊和基于同义词的多关键字排名搜索,从而将用户搜索体验提升到了最重要的水平,从而使加密搜索体验更接近免费文本搜索引擎。通过利用基于二叉树的动态索引,该方案与现有方案相比还改善了索引生成时间和搜索时间。实验结果证明了该提议方案的有效性,因为与之相比,该方案将搜索时间(即查找所需文档的时间)减少了90%,并且在需要上传新文件时(索引生成时间)使索引更新的开销最小化。文献中针对相似数据集的现有有效索引方案。之前尚未达到搜索时间和索引生成时间的优化。

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