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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.
Linköpings universitet, Institutionen för datavetenskap, Databas och informationsteknik. Linköpings universitet, Tekniska fakulteten.
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2020 (Engelska)Ingår i: Future Generation Computer Systems, ISSN 0167-739X, E-ISSN 1872-7115, Vol. 102, s. 382-392Artikel i tidskrift (Refereegranskat) 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.

Ort, förlag, år, upplaga, sidor
ELSEVIER , 2020. Vol. 102, s. 382-392
Nyckelord [en]
Trajectory data; Blockchain technology; Privacy preservation; Decentralised trajectory mining
Nationell ämneskategori
Datavetenskap (datalogi)
Identifikatorer
URN: urn:nbn:se:liu:diva-162911DOI: 10.1016/j.future.2019.07.068ISI: 000501936300031OAI: oai:DiVA.org:liu-162911DiVA, id: diva2:1382392
Anmärkning

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]

Tillgänglig från: 2020-01-02 Skapad: 2020-01-02 Senast uppdaterad: 2024-09-04

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Sodhro, Ali Hassan
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