Tree Proof-of-Position Algorithms

TL;DR

This paper introduces Tree-Proof-of-Position (T-PoP), a decentralized, privacy-preserving, and resilient algorithm for verifying agent positions, suitable for secure IoT applications and adversarial environments, supported by mathematical modeling and simulations.

Contribution

The paper presents a novel Tree-Proof-of-Position algorithm that is decentralized, privacy-preserving, and resilient to adversarial behavior, with validated mathematical modeling and simulations.

Findings

T-PoP is resilient to malicious agents.

The algorithm has quadratic runtime, suitable for IoT devices.

Mathematical models align with simulation results.

Abstract

We present a novel class of proof-of-position algorithms: Tree-Proof-of-Position (T-PoP). This algorithm is 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. Our algorithm is therefore resilient to highly adversarial scenarios. This makes it suitable for a wide class of applications, namely those in which 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. We then simulate T-PoP's behaviour with a large number of agent-based simulations, which are in complete agreement with our mathematical model, thus demonstrating its validity. 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.