Geodesic
Efficiency measurement system for zk-SNARK circuits internal representation
Prikladnaya Diskretnaya Matematika. Supplement, no. 17 (2024), pp. 129-131.

Voir la notice de l'article provenant de la source Math-Net.Ru

A software system for measuring the efficiency of zk-SNARK circuits internal representation has been developed. The system is designed to measure the parameters of zk-SNARK zero-knowledge proof circuits: the number of constraints in the rank 1 constraint systems (R1CS), the time of protocol initialization phase, the time of proof generation, and the lengths of the proving keys. The system allows zk-SNARK circuit developers to measure various parameters during the circuit coding phase and optimize constraint system representations. The developed software system can be used to measure the efficiency of arbitrary zk-SNARK circuits and determine their suitability for various applications.
Keywords: zero-knowledge proof, zk-SNARK, R1CS, algorithm efficiency.
Mots-clés : ZoKrates 
@article{PDMA_2024_17_a31,
     author = {D. O. Kondyrev},
     title = {Efficiency measurement system for {zk-SNARK} circuits internal representation},
     journal = {Prikladnaya Diskretnaya Matematika. Supplement},
     pages = {129--131},
     publisher = {mathdoc},
     number = {17},
     year = {2024},
     language = {ru},
     url = {http://geodesic.mathdoc.fr/item/PDMA_2024_17_a31/}
}
TY  - JOUR
AU  - D. O. Kondyrev
TI  - Efficiency measurement system for zk-SNARK circuits internal representation
JO  - Prikladnaya Diskretnaya Matematika. Supplement
PY  - 2024
SP  - 129
EP  - 131
IS  - 17
PB  - mathdoc
UR  - http://geodesic.mathdoc.fr/item/PDMA_2024_17_a31/
LA  - ru
ID  - PDMA_2024_17_a31
ER  - 
%0 Journal Article
%A D. O. Kondyrev
%T Efficiency measurement system for zk-SNARK circuits internal representation
%J Prikladnaya Diskretnaya Matematika. Supplement
%D 2024
%P 129-131
%N 17
%I mathdoc
%U http://geodesic.mathdoc.fr/item/PDMA_2024_17_a31/
%G ru
%F PDMA_2024_17_a31
D. O. Kondyrev. Efficiency measurement system for zk-SNARK circuits internal representation. Prikladnaya Diskretnaya Matematika. Supplement, no. 17 (2024), pp. 129-131. http://geodesic.mathdoc.fr/item/PDMA_2024_17_a31/

[1] Ben-Sasson E., Chiesa A., Genkin D., et al., “SNARKs for C: Verifying program executions succinctly and in zero knowledge”, LNCS, 8043 (2013), 90–108 | MR | Zbl

[2] Eberhardt J., Scalable and Privacy-preserving Off-chain Computations, Ph.D. Thesis, Technical University of Berlin, Faculty IV — Electrical Engineering and Computer Science, 2021, 284 pp.

[3] Eberhardt J. and Tai S., “ZoKrates — scalable privacy-preserving off-chain computations”, IEEE Intern. Conf. Blockchain (Halifax, Canada), 2018, 1084–1091