Decentralized Proof-of-Location for Content Provenance: Towards Capture-Time Authenticity

2026-03-29

AI Summary

This work addresses the challenge of ensuring data authenticity at the time of collection in adversarial or incentive-misaligned cyber-physical systems, where conventional device-centric provenance mechanisms fall short. To overcome this limitation, the paper proposes a decentralized witness zone architecture that extends Proof-of-Location into a multi-party collaborative verification protocol. By leveraging multiple independent observers to jointly generate auditable evidence artifacts, the approach guarantees data integrity without relying on a trusted third party. The proposed method substantially strengthens defenses against fabricated or staged events. Simulation experiments demonstrate that, in representative scenarios, the architecture effectively enhances the trustworthiness and tamper resistance of sensor data.

Abstract

Reliable use of real-world data requires confidence that recorded evidence reflects what actually occurred at the moment of capture. In adversarial or incentive-misaligned cyber-physical settings, device-centric provenance and post-capture verification are insufficient to provide that guarantee. This paper builds on Proof-of-Location (PoL) as a baseline for establishing where and when events take place, and extends it with a witnessing-zone architecture in which multiple independent observers collectively validate physical events. The resulting approach produces auditable evidence artifacts that can support downstream systems in cyber-physical settings, without relying on centralized trust. Through representative scenarios and simulation-based evaluation, this paper shows how such architectures improve sensor data trustworthiness and resilience to fabricated or staged events.

Problem

• Proof-of-Location
• content provenance
• capture-time authenticity
• cyber-physical systems
• trustworthiness

Innovation

• Decentralized Proof-of-Location
• Witnessing-Zone Architecture
• Content Provenance
• Capture-Time Authenticity
• Cyber-Physical Trust