Tree proof-of-position algorithms
File(s)
Accepted version
Author(s)
Kharman, Aida Manzano
Ferraro, Pietro
Hamedmoghadam, Homayoun
Shorten, Robert
Type
Journal Article
Abstract
A growing issue across multiple fields involves verifying that an individual or object is truly in the location it claims to be and, despite the significance of this problem, the scientific community has not extensively explored how to provide proof for such claims. Accordingly, this paper presents a novel class of proof-of-position algorithms: Tree-Proof-of-Position (T-PoP). These algorithms are decentralised, collaborative and can be computed in a privacy preserving manner, such that agents do not need to reveal their position publicly. We make no assumptions of honest behaviour in the system, and consider varying ways in which agents may misbehave. T-PoP is therefore resilient to adversarial scenarios, which makes it suitable for a wide class of applications, namely those where trust in a centralised infrastructure may not be assumed, or high security risk scenarios. Our algorithm has a worst case quadratic runtime, making it suitable for hardware constrained IoT applications. We also provide a mathematical model that summarises T-PoP’s performance for varying operating conditions. Using a large number of agent-based simulations, we verify the agreement between TPoP’s performance and our mathematical predictions. T-PoP can achieve high levels of reliability and security by tuning its operating conditions, both in high and low density environments. Finally, we also present a mathematical model to probabilistically detect platooning attacks.
Date Issued
2025-06-01
Date Acceptance
2025-01-01
Citation
IEEE Internet of Things Journal, 2025, (11), pp.16393-16409
ISSN
2327-4662
Publisher
Institute of Electrical and Electronics Engineers
Start Page
16393
End Page
16409
Journal / Book Title
IEEE Internet of Things Journal
Issue
11
Copyright Statement
Copyright © 2024 IEEE. This is the author’s accepted manuscript made available under a CC-BY licence in accordance with Imperial’s Research Publications Open Access policy (www.imperial.ac.uk/oa-policy)
License URL
Publication Status
Published
Date Publish Online
2025-01-20