The privacy protection algorithm of ciphertext nearest neighbor query based on the single Hilbert curve

计算机科学 希尔伯特曲线 密文 k-最近邻算法 算法 加密 人工智能 计算机安全
作者
Daniel Tan,Huajun Wang
出处
期刊:Ksii Transactions on Internet and Information Systems [Korea Society of Internet Information]
卷期号:16 (9)
标识
DOI:10.3837/tiis.2022.09.014
摘要

Nearest neighbor query in location-based services has become a popular application.Aiming at the shortcomings of the privacy protection algorithms of traditional ciphertext nearest neighbor query having the high system overhead because of the usage of the double Hilbert curves and having the inaccurate query results in some special circumstances, a privacy protection algorithm of ciphertext nearest neighbor query which is based on the single Hilbert curve has been proposed.This algorithm uses a single Hilbert curve to transform the two-dimensional coordinates of the points of interest into Hilbert values, and then encrypts them by the order preserving encryption scheme to obtain the one-dimensional ciphertext data which can be compared in numerical size.Then stores the points of interest as elements composed of index value and the ciphertext of the other information about the points of interest on the server-side database.When the user needs to use the nearest neighbor query, firstly calls the approximate nearest neighbor query algorithm proposed in this paper to query on the server-side database, and then obtains the approximate nearest neighbor query results.After that, the accurate nearest neighbor query result can be obtained by calling the precision processing algorithm proposed in this paper.The experimental results show that this privacy protection algorithm of ciphertext nearest neighbor query which is based on the single Hilbert curve is not only feasible, but also optimizes the system overhead and the accuracy of ciphertext nearest neighbor query result.
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