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Status已发表Published
TitleA decentralised approach to privacy preserving trajectory mining
Creator
Date Issued2020
Source PublicationFuture Generation Computer Systems
ISSN0167-739X
Volume102Pages:382-392
Abstract

Large volumes of mobility data is collected in various application domains. Enterprise applications are designed on the notion of centralised data control where the proprietary of the data rests with the enterprise and not with the user. This has consequences as evident by the occasional privacy breaches. Trajectory mining is an important data mining problem, however, trajectory data can disclose sensitive location information about users. In this work, we propose a decentralised blockchain-enabled privacy-preserving trajectory data mining framework where the proprietary of the data rests with the user and not with the enterprise. We formalise the privacy preservation in trajectory data mining settings, present a proposal for privacy preservation, and implement the solution as a proof-of-concept. A comprehensive experimental evaluation is conducted to assess the applicability of the system. The results show that the proposed system yields promising results for blockchain-enabled privacy preservation in user trajectory data.

KeywordBlockchain technology Decentralised trajectory mining Privacy preservation Trajectory data
DOI10.1016/j.future.2019.07.068
URLView source
Indexed BySCIE
Language英语English
WOS Research AreaComputer Science
WOS SubjectComputer Science, Theory & Methods
WOS IDWOS:000501936300031
Scopus ID2-s2.0-85071400133
Citation statistics
Cited Times:45[WOS]   [WOS Record]     [Related Records in WOS]
Document TypeJournal article
Identifierhttp://repository.uic.edu.cn/handle/39GCC9TT/6879
CollectionResearch outside affiliated institution
Corresponding AuthorLuo, Zongwei
Affiliation
1.Department of Computer Science,Bahria University,Islamabad,Pakistan
2.ECE Department,Nazarbayev University,Astana,Kazakhstan
3.University of Jordan,Amman,Jordan
4.University of Science and Technology Beijing,Beijing,China
5.IDA-Computer and Information Science Department,Linkoping University,Sweden
6.Department of Computer Science and Engineering,Southern University of Science and Technology,Shenzhen,China
7.Shenzhen Institutes of Advanced Technology,Chinese Academy of Sciences,Shenzhen,China
Recommended Citation
GB/T 7714
Talat, Romana,Obaidat, Mohammad S.,Muzammal, Muhammadet al. A decentralised approach to privacy preserving trajectory mining[J]. Future Generation Computer Systems, 2020, 102: 382-392.
APA Talat, Romana, Obaidat, Mohammad S., Muzammal, Muhammad, Sodhro, Ali Hassan, Luo, Zongwei, & Pirbhulal, Sandeep. (2020). A decentralised approach to privacy preserving trajectory mining. Future Generation Computer Systems, 102, 382-392.
MLA Talat, Romana,et al."A decentralised approach to privacy preserving trajectory mining". Future Generation Computer Systems 102(2020): 382-392.
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