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A decentralised approach to privacy preserving trajectory mining
Bahria Univ, Pakistan.
Nazarbayev Univ, Kazakhstan; Univ Jordan, Jordan; Univ Sci and Technol Beijing, Peoples R China.
Bahria Univ, Pakistan.
Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, Faculty of Science & Engineering.
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2020 (English)In: Future Generation Computer Systems, ISSN 0167-739X, E-ISSN 1872-7115, Vol. 102, p. 382-392Article in journal (Refereed) Published
Abstract [en]

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. (C) 2019 Elsevier B.V. All rights reserved.

Place, publisher, year, edition, pages
ELSEVIER , 2020. Vol. 102, p. 382-392
Keywords [en]
Trajectory data; Blockchain technology; Privacy preservation; Decentralised trajectory mining
National Category
Computer Sciences
Identifiers
URN: urn:nbn:se:liu:diva-162911DOI: 10.1016/j.future.2019.07.068ISI: 000501936300031OAI: oai:DiVA.org:liu-162911DiVA, id: diva2:1382392
Note

Funding Agencies|HEC Pakistan under the START-UP RESEARCH GRANT PROGRAM (SRGP) [21-1465/SRGP/RD/HEC/2016]; Sukkur IBA University, Sukkur, Sindh, Pakistan; Technologies and Equipment Guangdong Education Bureau Fund [2017KTSCX166]; Science and Technology Innovation Committee Foundation of Shenzhen [JCYJ201708171 12037041, ZDSYS20170303 1748284002E]

Available from: 2020-01-02 Created: 2020-01-02 Last updated: 2024-09-04

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CiteExportLink to record
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Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • oxford
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf