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Updatable privacy-preserving [Formula: see text] -nearest neighbor query in location-based s-ervice
The [Formula: see text] -nearest neighbor ([Formula: see text] -NN) query is an important query in location-based service (LBS), which can query the nearest k points to a given point, and provide some convenient services such as interest recommendations. Hence the privacy protection issue of [Formul...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer US
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8739704/ https://www.ncbi.nlm.nih.gov/pubmed/35018203 http://dx.doi.org/10.1007/s12083-021-01290-4 |
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author | Wu, Songyang Xu, Wenju Hong, Zhiyong Duan, Pu Zhang, Benyu Hu, Yupu Wang, Baocang |
author_facet | Wu, Songyang Xu, Wenju Hong, Zhiyong Duan, Pu Zhang, Benyu Hu, Yupu Wang, Baocang |
author_sort | Wu, Songyang |
collection | PubMed |
description | The [Formula: see text] -nearest neighbor ([Formula: see text] -NN) query is an important query in location-based service (LBS), which can query the nearest k points to a given point, and provide some convenient services such as interest recommendations. Hence the privacy protection issue of [Formula: see text] -NN query has been a popular research area, protecting the information of queries and the queried results, especially in the information era. However, most of existing schemes fail to consider the privacy protection of location points already stored on servers. Or some schemes support no update of location points. In this paper, we present an updatable and privacy-preserving [Formula: see text] -NN query scheme to address the above two issues. Concretely, our scheme utilizes the [Formula: see text] D-tree ([Formula: see text] -Dimensional tree) to store the location points of data owners in location service provider and encrypts the points with a distributed double-trapdoor public-key cryptosystem. Then, based on the Ciphertext Comparison Protocol and Ciphertext Euclidean Distance Calculation Protocol, our scheme can protect the privacy of location and query contents. Experimental analyses show our proposal supports some new location points for a fixed location service provider. Moreover, the queried results show a high accuracy of more than 95%. |
format | Online Article Text |
id | pubmed-8739704 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Springer US |
record_format | MEDLINE/PubMed |
spelling | pubmed-87397042022-01-07 Updatable privacy-preserving [Formula: see text] -nearest neighbor query in location-based s-ervice Wu, Songyang Xu, Wenju Hong, Zhiyong Duan, Pu Zhang, Benyu Hu, Yupu Wang, Baocang Peer Peer Netw Appl Article The [Formula: see text] -nearest neighbor ([Formula: see text] -NN) query is an important query in location-based service (LBS), which can query the nearest k points to a given point, and provide some convenient services such as interest recommendations. Hence the privacy protection issue of [Formula: see text] -NN query has been a popular research area, protecting the information of queries and the queried results, especially in the information era. However, most of existing schemes fail to consider the privacy protection of location points already stored on servers. Or some schemes support no update of location points. In this paper, we present an updatable and privacy-preserving [Formula: see text] -NN query scheme to address the above two issues. Concretely, our scheme utilizes the [Formula: see text] D-tree ([Formula: see text] -Dimensional tree) to store the location points of data owners in location service provider and encrypts the points with a distributed double-trapdoor public-key cryptosystem. Then, based on the Ciphertext Comparison Protocol and Ciphertext Euclidean Distance Calculation Protocol, our scheme can protect the privacy of location and query contents. Experimental analyses show our proposal supports some new location points for a fixed location service provider. Moreover, the queried results show a high accuracy of more than 95%. Springer US 2022-01-07 2022 /pmc/articles/PMC8739704/ /pubmed/35018203 http://dx.doi.org/10.1007/s12083-021-01290-4 Text en © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2022 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. |
spellingShingle | Article Wu, Songyang Xu, Wenju Hong, Zhiyong Duan, Pu Zhang, Benyu Hu, Yupu Wang, Baocang Updatable privacy-preserving [Formula: see text] -nearest neighbor query in location-based s-ervice |
title | Updatable privacy-preserving [Formula: see text] -nearest neighbor query in location-based s-ervice |
title_full | Updatable privacy-preserving [Formula: see text] -nearest neighbor query in location-based s-ervice |
title_fullStr | Updatable privacy-preserving [Formula: see text] -nearest neighbor query in location-based s-ervice |
title_full_unstemmed | Updatable privacy-preserving [Formula: see text] -nearest neighbor query in location-based s-ervice |
title_short | Updatable privacy-preserving [Formula: see text] -nearest neighbor query in location-based s-ervice |
title_sort | updatable privacy-preserving [formula: see text] -nearest neighbor query in location-based s-ervice |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8739704/ https://www.ncbi.nlm.nih.gov/pubmed/35018203 http://dx.doi.org/10.1007/s12083-021-01290-4 |
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