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Secure $k$k-NN Query on Encrypted Cloud Data with Multiple Keys

机译:secure $ k $ $ <替代品> k < / renternativings>/inline-formula>-nn查询加密云数据与多个键

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摘要

The k-nearest neighbors (k-NN) query is a fundamental primitive in spatial and multimedia databases. It has extensive applications in location-based services, classification & clustering and so on. With the promise of confidentiality and privacy, massive data are increasingly outsourced to cloud in the encrypted form for enjoying the advantages of cloud computing (e.g., reduce storage and query processing costs). Recently, many schemes have been proposed to support k-NN query on encrypted cloud data. However, prior works have all assumed that the query users (QUs) are fully-trusted and know the key of the data owner (DO), which is used to encrypt and decrypt outsourced data. The assumptions are unrealistic in many situations, since many users are neither trusted nor knowing the key. In this paper, we propose a novel scheme for secure k-NN query on encrypted cloud data with multiple keys, in which the DO and each QU all hold their own different keys, and do not share them with each other; meanwhile, the DO encrypts and decrypts outsourced data using the key of his own. Our scheme is constructed by a distributed two trapdoors public-key cryptosystem (DT-PKC) and a set of protocols of secure two-party computation, which not only preserves the data confidentiality and query privacy but also supports the offline data owner. Our extensive theoretical and experimental evaluations demonstrate the effectiveness of our scheme in terms of security and performance.
机译:K-Collect邻居(K-NN)查询是空间和多媒体数据库中的基本原语。它在基于位置的服务,分类和聚类等方面具有广泛的应用程序。凭借保密性和隐私的承诺,大规模数据越来越多地将云以加密形式云,以享受云计算的优势(例如,降低存储和查询处理成本)。最近,已经提出了许多方案来支持加密云数据的K-NN查询。但是,先前的作品都假定查询用户(QUS)是完全信任的,并知道数据所有者(DO)的密钥,用于加密和解密外包数据。许多情况下,假设是不现实的,因为许多用户都不是值得信赖的,也不知道密钥。在本文中,我们提出了一种新的方案,用于使用多个键对加密云数据查询的安全k-nn查询,其中每个曲线都持有自己的不同键,并且不与彼此共享;同时,DO使用自己的密钥加密和解密外包数据。我们的方案由分布式的两个陷波图公钥密码系统(DT-PKC)和一组安全的双方计算协议,不仅保留了数据机密性和查询隐私,而且还支持脱机数据所有者。我们广泛的理论和实验评估展示了我们方案在安全性和表现方面的有效性。

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  • 来源
    《Big Data, IEEE Transactions on》 |2021年第4期|689-702|共14页
  • 作者单位

    Xidian Univ Sch Comp Sci & Technol Xian 710071 Shaanxi Peoples R China|Anhui Univ Sch Comp Sci & Technol Hefei 230601 Anhui Peoples R China;

    Xidian Univ Sch Comp Sci & Technol Xian 710071 Shaanxi Peoples R China;

    Xidian Univ Sch Comp Sci & Technol Xian 710071 Shaanxi Peoples R China;

    Victoria Univ Coll Engn & Sci Ctr Appl Informat Footscray Vic 3011 Australia|Taiyuan Normal Univ Dept Comp Sci Jinzhong 030619 Peoples R China;

    Xidian Univ Sch Comp Sci & Technol Xian 710071 Shaanxi Peoples R China;

    Xidian Univ Sch Comp Sci & Technol Xian 710071 Shaanxi Peoples R China|Future Univ Hakodate Sch Syst Informat Sci 116-2 Kameda Nakano Cho Hakodate Hokkaido 0418655 Japan;

    Xidian Univ Sch Comp Sci & Technol Xian 710071 Shaanxi Peoples R China;

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  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Data security; k-NN query; multiple keys; cloud computing;

    机译:数据安全;k-nn查询;多个键;云计算;

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