Paper 2019/1494
Scaling Verifiable Computation Using Efficient Set Accumulators
Alex Ozdemir, Riad S. Wahby, Barry Whitehat, and Dan Boneh
Abstract
Verifiable outsourcing systems offload a large computation to a remote server, but require that the remote server provide a succinct proof, called a SNARK, that proves that the server carried out the computation correctly. Real-world applications of this approach can be found in several blockchain systems that employ verifiable outsourcing to process a large number of transactions off-chain. This reduces the on-chain work to simply verifying a succinct proof that transaction processing was done correctly. In practice, verifiable outsourcing of state updates is done by updating the leaves of a Merkle tree, recomputing the resulting Merkle root, and proving using a SNARK that the state update was done correctly. In this work, we use a combination of existing and novel techniques to implement an RSA accumulator inside of a SNARK, and use it as a replacement for a Merkle tree. We specifically optimize the accumulator for compatibility with SNARKs. Our experiments show that the resulting system reduces costs compared to existing approaches that use Merkle trees for committing to the current state. These results apply broadly to any system that needs to offload batches of state updates to an untrusted server.
Note: camera-ready version
Metadata
- Available format(s)
-
PDF
- Category
- Implementation
- Publication info
- Preprint. MINOR revision.
- Keywords
- SNARKsRSAMerkleAccumulators
- Contact author(s)
- aozdemir @ cs stanford edu
- History
- 2020-06-23: last of 2 revisions
- 2019-12-30: received
- See all versions
- Short URL
- https://ia.cr/2019/1494
- License
-
CC BY
BibTeX
@misc{cryptoeprint:2019/1494,
author = {Alex Ozdemir and Riad S. Wahby and Barry Whitehat and Dan Boneh},
title = {Scaling Verifiable Computation Using Efficient Set Accumulators},
howpublished = {Cryptology {ePrint} Archive, Paper 2019/1494},
year = {2019},
url = {https://eprint.iacr.org/2019/1494}
}
