Lattice-Based Commitment Scheme for Proving Linear Relations between Hidden Values

A hybrid lattice-based commitment scheme is proposed for anonymous proofs between hidden values. The method is based on a modification of the BDLOP zero-knowledge proof (ZKP) scheme by replacing the learning with errors (LWE) problem with a learning with rounding (LWR) problem, which theoretically makes it possible to reduce the size of the parameters and reduce the complexity of parameter selection. It is shown that the proposed scheme preserves the property of additive homomorphism, which makes it possible to apply it to prove linear relations. The obtained results can be applied to construct electronic voting protocols or conduct anonymous transactions.

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Publication Details

Journal
Automatic Control and Computer Sciences
Published
2025-12-01
DOI
https://doi.org/10.3103/s0146411625700944
Primary Topic
Cryptography and Data Security
Type
article
Field-Weighted Citation Impact
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article

Lattice-Based Commitment Scheme for Proving Linear Relations between Hidden Values

E. B. Aleksandrova, D. M. Samareva
Automatic Control and Computer Sciences
Cryptography and Data Security
article

Lattice-Based Commitment Scheme for Proving Linear Relations between Hidden Values

E. B. Aleksandrova, D. M. Samareva
article en

Abstract

A hybrid lattice-based commitment scheme is proposed for anonymous proofs between hidden values. The method is based on a modification of the BDLOP zero-knowledge proof (ZKP) scheme by replacing the learning with errors (LWE) problem with a learning with rounding (LWR) problem, which theoretically makes it possible to reduce the size of the parameters and reduce the complexity of parameter selection. It is shown that the proposed scheme preserves the property of additive homomorphism, which makes it possible to apply it to prove linear relations. The obtained results can be applied to construct electronic voting protocols or conduct anonymous transactions.

Automatic Control and Computer SciencesVol. 59(8)
Peter the Great St. Petersburg Polytechnic University (RU)
Peace, Justice and strong institutions
Openalex Percentile: Top 14%
Cryptography and Data Security
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