zk-PoT: Zero-Knowledge Proof of Traffic for Privacy Enabled Cooperative Perception

TL;DR

This paper introduces zk-PoT, a zero-knowledge proof system for vehicle traffic data that enhances privacy and authenticity verification in cooperative perception for connected vehicles, without relying on trust-based methods.

Contribution

The paper proposes a novel cryptographic approach using zero-knowledge proofs based on vehicle number plates to verify data authenticity without prior trust or plausibility checks.

Findings

Achieves 70-80% verification success rate during rush hours.

Prevents most common attacks, mitigates collusion attacks.

Compatible with existing ITS standards.

Abstract

Cooperative perception is an essential and widely discussed application of connected automated vehicles. However, the authenticity of perception data is not ensured, because the vehicles cannot independently verify the event they did not see. Many methods, including trust-based (i.e., statistical) approaches and plausibility-based methods, have been proposed to determine data authenticity. However, these methods cannot verify data without a priori knowledge. In this study, a novel approach of constructing a self-proving data from the number plate of target vehicles was proposed. By regarding the pseudonym and number plate as a shared secret and letting multiple vehicles prove they know it independently, the data authenticity problem can be transformed to a cryptography problem that can be solved without trust or plausibility evaluations. Our work can be adapted to the existing works including ETSI/ISO ITS standards while maintaining backward compatibility. Analyses of common attacks and attacks specific to the proposed method reveal that most attacks can be prevented, whereas preventing some other attacks, such as collusion attacks, can be mitigated. Experiments based on realistic data set show that the rate of successful verification can achieve 70\% to 80\% at rush hours.