HilAnchor：Location Privacy Protection in the Presence of Users＇ Preferences

Location privacy receives considerable attentions in emerging location based services.Most current practices however either ignore users＇ preferences or incompletely fulfill privacy preferences.In this paper,we propose a privacy protection solution to allow users＇ preferences in the fundamental quer...

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Bibliographic Details
Published inJournal of computer science and technology Vol. 27; no. 2; pp. 413 - 427
Main Author 倪巍伟 郑锦旺 崇志宏
Format Journal Article
LanguageEnglish
Published Boston Springer US 01.03.2012
Springer Nature B.V
School of Computer Science and Engineering,Southeast University,Nanjing 210096,China%Key Laboratory of Computer Network and Information Integration in Southeast University,Ministry of Education Nanjing 210096,China
Subjects
Analysis
Artificial Intelligence
Clustering
Communication
Computer Science
Data compression
Data Structures and Information Theory
Flexibility
Hilbert curve
Hilbert space
Hilbert曲线
Information Systems Applications (incl.Internet)
Location based services
Mathematical models
Position (location)
Preferences
Privacy
Queries
Query processing
Regular Paper
Servers
Software Engineering
Studies
Theory of Computation
Transformations
Workload
Workloads
可扩展性
基于位置的服务
用户
空间时间
聚类特性
通信成本
隐私保护
NN query
location privacy
users' privacy preferences
minimum inferred region
kNN query
Online AccessGet full text
ISSN1000-9000
1860-4749
DOI10.1007/s11390-012-1231-2

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Summary:Location privacy receives considerable attentions in emerging location based services.Most current practices however either ignore users＇ preferences or incompletely fulfill privacy preferences.In this paper,we propose a privacy protection solution to allow users＇ preferences in the fundamental query of k nearest neighbors （kNN）.Particularly,users are permitted to choose privacy preferences by specifying minimum inferred region.Via Hilbert curve based transformation,the additional workload from users＇ preferences is alleviated.Furthermore,this transformation reduces time-expensive region queries in 2-D space to range the ones in 1-D space.Therefore,the time efficiency,as well as communication efficiency,is greatly improved due to clustering properties of Hilbert curve.Further,details of choosing anchor points are theoretically elaborated.The empirical studies demonstrate that our implementation delivers both flexibility for users＇ preferences and scalability for time and communication costs.
Bibliography:11-2296/TP
Location privacy receives considerable attentions in emerging location based services.Most current practices however either ignore users＇ preferences or incompletely fulfill privacy preferences.In this paper,we propose a privacy protection solution to allow users＇ preferences in the fundamental query of k nearest neighbors （kNN）.Particularly,users are permitted to choose privacy preferences by specifying minimum inferred region.Via Hilbert curve based transformation,the additional workload from users＇ preferences is alleviated.Furthermore,this transformation reduces time-expensive region queries in 2-D space to range the ones in 1-D space.Therefore,the time efficiency,as well as communication efficiency,is greatly improved due to clustering properties of Hilbert curve.Further,details of choosing anchor points are theoretically elaborated.The empirical studies demonstrate that our implementation delivers both flexibility for users＇ preferences and scalability for time and communication costs.
Wei-Wei Ni, Jin-Wang Zheng Zhi-Hong Chong（School of Computer Science and Engineering, Southeast University, Nanjing 210096, China Key Laboratory of Computer Network and Information Integration in Southeast University, Ministry of Education Nanjing 210096, China
location privacy,kNN query,minimum inferred region,users＇ privacy preferences
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ISSN:1000-9000
1860-4749
DOI:10.1007/s11390-012-1231-2