Tree Proof-of-Position Algorithms

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 article presents a novel class of proof-of-position algorithms: tree-proof-of-position (T-PoP). These algorithms are decentralized, 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 behavior 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 centralized 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 summarizes 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.