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带保密性的位置数据的高效聚合查询。

Efficient Aggregate Queries on Location Data with Confidentiality.

机构信息

Software College, Northeastern University, Shenyang 110000, China.

出版信息

Sensors (Basel). 2022 Jun 29;22(13):4908. doi: 10.3390/s22134908.

Abstract

Location data have great value for facility location selection. Due to the privacy issues of both location data and user identities, a location service provider can not hand over the private location data to a business or a third party for analysis or reveal the location data for jointly running data analysis with a business. In this paper, we propose a newly constructed PSI filter that can help the two parties privately find the data corresponding to the items in the intersection without any computations and, subsequently, we give the PSI filter generation protocol. We utilize it to construct three types of aggregate protocols for facility location selection with confidentiality. Then we propose a ciphertext matrix compressing method, making one block of cipher contain lots of plaintext data while keeping the homomorphic property valid. This method can efficiently further reduce the computation/communication cost of the query process-the improved query protocol utilizing the ciphertext matrix compressing method is given followed. We show the correctness and privacy of the proposed query protocols. The theoretical analysis of computation/communication overhead shows that our proposed query protocols are efficient both in computation and communication and the experimental results of the efficiency tests show the practicality of the protocols.

摘要

位置数据对于设施选址具有重要价值。由于位置数据和用户身份的隐私问题,位置服务提供商不能将私人位置数据交给企业或第三方进行分析,也不能与企业共同运行数据共享位置数据。在本文中,我们提出了一种新的 PSI 过滤器,可以帮助双方在不进行任何计算的情况下私下找到相交项对应的数据,然后给出 PSI 过滤器生成协议。我们利用它构建了三种具有保密性的设施选址聚合协议。然后,我们提出了一种密文矩阵压缩方法,使得一个块的密文包含大量的明文数据,同时保持同态属性的有效性。这种方法可以有效地进一步降低查询过程的计算/通信成本,随后给出了利用密文矩阵压缩方法改进的查询协议。我们证明了所提出的查询协议的正确性和隐私性。计算/通信开销的理论分析表明,我们提出的查询协议在计算和通信方面都具有效率,效率测试的实验结果表明了协议的实用性。

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