CRQUANT-PHDec 18, 2020

Experimental relativistic zero-knowledge proofs

arXiv:2012.10452v216 citations
Originality Highly original
AI Analysis

This work provides a practical demonstration of a multi-prover zero-knowledge protocol, offering a new method for secure identification and blockchain applications without relying on computational assumptions, which is significant for users concerned about data breaches.

This paper experimentally demonstrates a relativistic zero-knowledge proof protocol, allowing a prover to convince a verifier of a statement's validity without revealing any secret information. The implementation, using off-the-shelf equipment, operates at distances from 60m to over 400m within approximately one second.

Protecting secrets is a key challenge in our contemporary information-based era. In common situations, however, revealing secrets appears unavoidable, for instance, when identifying oneself in a bank to retrieve money. In turn, this may have highly undesirable consequences in the unlikely, yet not unrealistic, case where the bank's security gets compromised. This naturally raises the question of whether disclosing secrets is fundamentally necessary for identifying oneself, or more generally for proving a statement to be correct. Developments in computer science provide an elegant solution via the concept of zero-knowledge proofs: a prover can convince a verifier of the validity of a certain statement without facilitating the elaboration of a proof at all. In this work, we report the experimental realisation of such a zero-knowledge protocol involving two separated verifier-prover pairs. Security is enforced via the physical principle of special relativity, and no computational assumption (such as the existence of one-way functions) is required. Our implementation exclusively relies on off-the-shelf equipment and works at both short (60 m) and long distances ($\geqslant$400 m) in about one second. This demonstrates the practical potential of multi-prover zero-knowledge protocols, promising for identification tasks and blockchain applications such as cryptocurrencies or smart contracts.

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