Efficient Query Verification for Blockchain Superlight Clients Using SNARKs

TL;DR

The paper tackles the challenge of verifiable data access for superlight blockchain clients by introducing Stateless Superlight Clients (SSLC) that perform application-specific map-reduce queries using SNARK proofs. The approach decomposes large queries into per-block sub-tasks, producing succinct proofs that can be verified with public information from full nodes, and then recursively aggregates these proofs to scale to large datasets. A key contribution is the combination of an existential-honesty assumption for full nodes with a two-phase SSLC protocol (query and verify), ensuring correctness while keeping storage, communication, and computation sublinear in the size of the transaction set. The authors demonstrate substantial practical benefits in Bitcoin and Ethereum use cases, showing orders-of-magnitude reductions in data transfer (e.g., under 5 MB for Bitcoin and around 9 MB for Ethereum) compared to traditional light-client approaches, and they validate performance through experiments using Plonky2 and recursive SNARKs. This work advances decentralized, verifiable, app-specific querying on blockchains, enabling reliable access on constrained devices such as smartphones without sacrificing decentralization.

Abstract

Blockchains are among the most powerful technologies to realize decentralized information systems. In order to safely enjoy all guarantees provided by a blockchain, one should maintain a full node, therefore maintaining an updated local copy of the ledger. This allows one to locally verify transactions, states of smart contracts, and to compute any information over them. Unfortunately, for obvious practical reasons, a very large part of blockchain-based information systems consists of users relying on clients that access data stored in blockchains only through servers, without verifying what is received. In notable use cases, the user has application-specific queries that can be answered only by very few servers, sometimes all belonging to the same organization. This clearly re-introduces a single point of failure. In this work we present an architecture allowing superlight clients (i.e., clients that do not want to download the involved transactions) to outsource the computation of a query to a (possibly untrusted) server, receiving a trustworthy answer. Our architecture relies on the power of SNARKs and makes them lighter to compute by using data obtained from full nodes and blockchain explorers, possibly leveraging the existence of smart contracts. The viability of our architecture is confirmed by an experimental evaluation on concrete scenarios. Our work paves the road towards blockchain-based information systems that remain decentralized and reliable even when users rely on common superlight clients (e.g., smartphones).

Figures (7)

• Figure 1: Current approaches to compute an application-specific query might be unfeasible on resource constrained devices, such as smart phones. Implementing complex queries on smart contracts can be unfeasible or result in prohibitive costs. Smart phones do not have sufficient space to download the whole blockchain and when handling the query requires large bandwidth and/or memory, also light clients might be unfeasible.
• Figure 2: In this example we are interested in computing the average value of all the transactions generated by users k1 and k2. For the sake of simplicity, we consider a mapper for each block. The SNARKs are used to prove the result of the computation. To prove all relevant transactions have been considered, the SNARK output is linked to a cumulative value available in a full node; in the example the toal number of involved transactions.
• Figure 3: Stateless Superlight Client Architecture.
• Figure 4: Computing steps of a Map-Reduce query.
• Figure 5: Description of the Query phase of the SSLC protocol.