Maximizing Privacy and Security of Collaborative Indoor Positioning using Zero-Knowledge Proofs

Simple item page
dc.contributor.authorCasanova-Marqués, Raúlcs
dc.contributor.authorTorres-Sospedra, Joaquíncs
dc.contributor.authorHajný, Jancs
dc.contributor.authorGould, Michaelcs
dc.coverage.issueneuvedenocs
dc.coverage.volume22cs
dc.date.issued2023-04-26cs
dc.description.abstractThe increasing popularity of wearable-based Collaborative Indoor Positioning Systems (CIPSs) has led to the development of new methods for improving positioning accuracy. However, these systems often rely on protocols, such as iBeacon, that lack sufficient privacy protection. In addition, they depend on centralized entities for the authentication and verification processes. To address the limitations of existing protocols, this paper presents a groundbreaking contribution to the field of wearable-based CIPSs. We propose a decentralized Attribute-based Authentication (ABA) protocol that offers superior levels of privacy protection, untraceability, and unlinkability of user actions. Unlike existing protocols that rely on centralized entities, our approach leverages decentralized mechanisms for authentication and verification, ensuring the privacy of user location data exchange. Through extensive experimentation across multiple platforms, our results demonstrate the practicality and feasibility of the proposed protocol for real-world deployment. Overall, this work opens up new avenues for secure and privacy-preserving wearable-based CIPSs, with potential implications for the rapidly growing field of Internet of Things (IoT) applications.en
dc.formattextcs
dc.format.extent1-18cs
dc.format.mimetypeapplication/pdfcs
dc.identifier.citationInternet of Things. 2023, vol. 22, issue neuvedeno, p. 1-18.en
dc.identifier.doi10.1016/j.iot.2023.100801cs
dc.identifier.issn2542-6605cs
dc.identifier.orcid0000-0001-6653-867Xcs
dc.identifier.orcid0000-0003-2831-1073cs
dc.identifier.other183357cs
dc.identifier.scopus55504712600cs
dc.identifier.urihttp://hdl.handle.net/11012/213639
dc.language.isoencs
dc.publisherElseviercs
dc.relation.ispartofInternet of Thingscs
dc.relation.urihttps://www.sciencedirect.com/science/article/pii/S2542660523001245cs
dc.rightsCreative Commons Attribution 4.0 Internationalcs
dc.rights.accessopenAccesscs
dc.rights.sherpahttp://www.sherpa.ac.uk/romeo/issn/2542-6605/cs
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/cs
dc.subjectAttribute-based Credentialsen
dc.subjectDecentralized Authenticationen
dc.subjectPrivacyen
dc.subjectAnonymityen
dc.subjectCollaborative Indoor Positioning Systemsen
dc.subjectBluetooth Low Energyen
dc.subjectWearablesen
dc.titleMaximizing Privacy and Security of Collaborative Indoor Positioning using Zero-Knowledge Proofsen
dc.type.driverarticleen
dc.type.statusPeer-revieweden
dc.type.versionpublishedVersionen
sync.item.dbidVAV-183357en
sync.item.dbtypeVAVen
sync.item.insts2025.02.03 15:42:33en
sync.item.modts2025.01.17 18:49:18en
thesis.grantorVysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií. Ústav telekomunikacícs
Files
Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
1s2.0S2542660523001245main.pdf
Size:
1.16 MB
Format:
Adobe Portable Document Format
Description:
1s2.0S2542660523001245main.pdf
Download
Collections
Ústav telekomunikací