Maximizing Privacy and Security of Collaborative Indoor Positioning using Zero-Knowledge Proofs
Identifikátory výsledku
Kód výsledku v IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26220%2F23%3APU148029" target="_blank" >RIV/00216305:26220/23:PU148029 - isvavai.cz</a>
Výsledek na webu
<a href="https://www.sciencedirect.com/science/article/pii/S2542660523001245" target="_blank" >https://www.sciencedirect.com/science/article/pii/S2542660523001245</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1016/j.iot.2023.100801" target="_blank" >10.1016/j.iot.2023.100801</a>
Alternativní jazyky
Jazyk výsledku
angličtina
Název v původním jazyce
Maximizing Privacy and Security of Collaborative Indoor Positioning using Zero-Knowledge Proofs
Popis výsledku v původním jazyce
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.
Název v anglickém jazyce
Maximizing Privacy and Security of Collaborative Indoor Positioning using Zero-Knowledge Proofs
Popis výsledku anglicky
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.
Klasifikace
Druh
J<sub>imp</sub> - Článek v periodiku v databázi Web of Science
CEP obor
—
OECD FORD obor
20202 - Communication engineering and systems
Návaznosti výsledku
Projekt
—
Návaznosti
S - Specificky vyzkum na vysokych skolach
Ostatní
Rok uplatnění
2023
Kód důvěrnosti údajů
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Údaje specifické pro druh výsledku
Název periodika
Internet of Things
ISSN
2542-6605
e-ISSN
—
Svazek periodika
22
Číslo periodika v rámci svazku
neuvedeno
Stát vydavatele periodika
NL - Nizozemsko
Počet stran výsledku
18
Strana od-do
1-18
Kód UT WoS článku
001053599100001
EID výsledku v databázi Scopus
2-s2.0-85159804362