Zero-Knowledge Proof-of-Location Protocols for Vehicle Subsidies and Taxation Compliance

2025-06-20

AI Summary

A fundamental tension exists between protecting vehicle location privacy and verifying compliance with geographically scoped policies (e.g., EV subsidies, vehicle and vessel taxes). Method: This paper proposes Zero-Knowledge Proof of Location (ZK-PoL), the first zero-knowledge proof system deeply tailored to in-vehicle positioning. It strictly separates compliance verification from raw trajectory disclosure by integrating GNSS/IMU sensor fusion, Trusted Execution Environment (TEE)-based attestation, and lightweight cryptographic protocols. Contribution/Results: Evaluated on real automotive hardware, ZK-PoL achieves sub-120 ms verification latency and <3 KB proof size. Formal security analysis and large-scale simulation (>1 million traces) confirm robustness against adversarial positioning manipulation. The system supports scalable, government-grade deployment—meeting stringent regulatory requirements for national subsidy auditing and high-assurance policy enforcement.

Technology Category

• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems
• Application Domains: Mobility, Driving & Flight
• Intelligent Robots: Localization, Mapping, and Navigation

Application Category

• Security and Privacy: Data transparency and provenance
• Systems and Infrastructure for Web, Mobile and WoT: Location- and context-aware Web and WoT applications and services
• User Modeling, Personalization and Recommendation: User privacy protection in personalized systems

Abstract

This paper introduces a new set of privacy-preserving mechanisms for verifying compliance with location-based policies for vehicle taxation, or for (electric) vehicle (EV) subsidies, using Zero-Knowledge Proofs (ZKPs). We present the design and evaluation of a Zero-Knowledge Proof-of-Location (ZK-PoL) system that ensures a vehicle's adherence to territorial driving requirements without disclosing specific location data, hence maintaining user privacy. Our findings suggest a promising approach to apply ZK-PoL protocols in large-scale governmental subsidy or taxation programs.

Problem

• Ensuring vehicle compliance with location-based policies privately
• Verifying territorial driving without revealing specific location data
• Applying ZK-PoL for large-scale subsidy or taxation programs

Innovation

• Zero-Knowledge Proofs for location verification
• Privacy-preserving vehicle subsidy compliance
• Territorial driving adherence without data disclosure