Publication detail

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

CASANOVA-MARQUES, R. TORRES-SOSPEDRA, J. HAJNY, J. GOULD, M.

Original Title

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

Type

journal article in Web of Science

Language

English

Original Abstract

The 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.

Keywords

Attribute-based Credentials, Decentralized Authentication, Privacy, Anonymity, Collaborative Indoor Positioning Systems, Bluetooth Low Energy, Wearables

Authors

CASANOVA-MARQUES, R.; TORRES-SOSPEDRA, J.; HAJNY, J.; GOULD, M.

Released

26. 4. 2023

Publisher

Elsevier

ISBN

2542-6605

Periodical

Internet of Things

Year of study

22

Number

neuvedeno

State

Kingdom of the Netherlands

Pages from

1

Pages to

18

Pages count

18

URL

https://www.sciencedirect.com/science/article/pii/S2542660523001245

Full text in the Digital Library

http://hdl.handle.net/11012/213639

BibTex

@article{BUT183357,
  author="Raúl {Casanova-Marqués} and Joaquín {Torres-Sospedra} and Jan {Hajný} and Michael {Gould}",
  title="Maximizing Privacy and Security of Collaborative Indoor Positioning using Zero-Knowledge Proofs",
  journal="Internet of Things",
  year="2023",
  volume="22",
  number="neuvedeno",
  pages="1--18",
  doi="10.1016/j.iot.2023.100801",
  issn="2542-6605",
  url="https://www.sciencedirect.com/science/article/pii/S2542660523001245"
}