Paper 2025/110
Verification-efficient Homomorphic Signatures for Verifiable Computation over Data Streams
, IMDEA Software Institute, Universidad Politécnica de Madrid, IMDEA Software Institute, IMDEA Software InstituteAbstract
Homomorphic signatures for NP (HSNP) allow proving that a signed value is the result of a non-deterministic computation on signed inputs. At CCS'22, Fiore and Tucker introduced HSNP, showed how to use them for verifying arbitrary computations on data streams, and proposed a generic HSNP construction obtained by efficiently combining zkSNARKs with linearly homomorphic signatures (LHS), namely those supporting linear functions. Their proposed LHS however suffered from an high verification cost. In this work we propose an efficient LHS that significantly improves on previous work in terms of verification time. Using the modular approach of Fiore and Tucker, this yields a verifier-efficient HSNP. We show that the HSNP instantiated with our LHS is particularly suited to the case when the data is taken from consecutive samples, which captures important use cases including sliding window statistics such as variances, histograms and stock market predictions.
Metadata
- Available format(s)
-
PDF
- Category
- Cryptographic protocols
- Publication info
- Published elsewhere. Major revision. Financial Cryptography and Data Security
- Keywords
- Verifiable Computationhomomorphic signatureszero-knowledge proofsSNARKsData StreamsData Privacy
- Contact author(s)
-
gaspard anthoine @ imdea org
daniele cozzo @ imdea org
dario fiore @ imdea org - History
- 2025-01-24: approved
- 2025-01-23: received
- See all versions
- Short URL
- https://ia.cr/2025/110
- License
-
CC BY
BibTeX
@misc{cryptoeprint:2025/110,
author = {Gaspard Anthoine and Daniele Cozzo and Dario Fiore},
title = {Verification-efficient Homomorphic Signatures for Verifiable Computation over Data Streams},
howpublished = {Cryptology {ePrint} Archive, Paper 2025/110},
year = {2025},
url = {https://eprint.iacr.org/2025/110}
}
