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MinHash-Based Fuzzy Keyword Search of Encrypted Data across Multiple Cloud Servers

机译:基于MinHash的跨多个云服务器的加密数据模糊关键字搜索

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To enhance the efficiency of data searching, most data owners store their data files in different cloud servers in the form of cipher-text. Thus, efficient search using fuzzy keywords becomes a critical issue in such a cloud computing environment. This paper proposes a method that aims at improving the efficiency of cipher-text retrieval and lowering storage overhead for fuzzy keyword search. In contrast to traditional approaches, the proposed method can reduce the complexity of Min-Hash-based fuzzy keyword search by using Min-Hash fingerprints to avoid the need to construct the fuzzy keyword set. The method will utilize Jaccard similarity to rank the results of retrieval, thus reducing the amount of calculation for similarity and saving a lot of time and space overhead. The method will also take consideration of multiple user queries through re-encryption technology and update user permissions dynamically. Security analysis demonstrates that the method can provide better privacy preservation and experimental results show that efficiency of cipher-text using the proposed method can improve the retrieval time and lower storage overhead as well.
机译:为了提高数据搜索的效率,大多数数据所有者以密文形式将其数据文件存储在不同的云服务器中。因此,在这种云计算环境中,使用模糊关键词的有效搜索成为关键问题。提出一种旨在提高密文检索效率,降低模糊关键词搜索存储开销的方法。与传统方法相比,该方法可以通过使用Min-Hash指纹来减少基于Min-Hash的模糊关键字搜索的复杂性,从而无需构造模糊关键字集。该方法将利用Jaccard相似度对检索结果进行排名,从而减少相似度的计算量并节省大量时间和空间开销。该方法还将通过重新加密技术考虑多个用户查询,并动态更新用户权限。安全性分析表明,该方法可以提供更好的隐私保护,实​​验结果表明,该方法能有效提高密文的检索时间,降低存储开销。

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