Subspace k-anonymity algorithm for location-privacy preservation based on locality-sensitive hashing-Reference-Cited by-同舟云学术

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Subspace k-anonymity algorithm for location-privacy preservation based on locality-sensitive hashing

Published:2019-10-24 Issue:5 Volume:23 Page:1167-1185
ISSN:1088-467X
Container-title:Intelligent Data Analysis
language:
Short-container-title:IDA

Author:

Wang Xiaohan¹²³,Luo Yonglong¹²³,Liu Shiyang³,Wang Taochun²³,Han Huihui²³

Affiliation:

1. School of Geography and Tourism, Anhui Normal University, Wuhu, Anhui 241002, China

2. School of Computer and Information, Anhui Normal University, Wuhu, Anhui 241002, China

3. Anhui Provincial Key Laboratory of Network and Information Security, Anhui Normal University, Wuhu, Anhui 241002, China

Publisher

IOS Press

Subject

Artificial Intelligence,Computer Vision and Pattern Recognition,Theoretical Computer Science

Reference39 articles.

1. Enhancing privacy through uniform grid and caching in location-based services;Zhang;Future Generation Computer Systems-the International Journal of Escience,2018

2. Messages in a concealed bottle: achieving query content privacy with accurate location-based services;Hu;IEEE Transactions on Vehicular Technology,2018

3. “I wasn’t there” Deniable, privacy-aware scheme for decentralized location-based services;Dimitriou;Future Generation Computer Systems-the International Journal of Escience,2018

4. From location to location pattern privacy in location-based services;Abul;Knowledge and Information Systems,2018

5. LPPS: A distributed cache pushing based k-anonymity location privacy preserving scheme;Chen;Mobile Information Systems,2016

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2. K-Implicit Tracking Data Publishing Scheme Against Geo-Matching Attacks;J INF SCI ENG;2022

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