The simplest possible SNARK for NP. You know, for kids!
This is a self-contained development of SNARKs for NP. It is based on Square Span Program SNARKs by Danezis et al., which are expressive enough to encode boolean circuits.
This code accompanies a tutorial on defining and analyzing the security of a SNARK, focusing on the soundness proof. (writeup.)
This is for educational purposes only. It's not efficient overall compared to state-of-the-art SNARK implementations, it doesn't come with a type system or any program analysis to rule out mistakes, and it doesn't support the zero-knowledge feature. It does, however, demonstrate some important SNARK design concepts and algorithm optimizations. It's succinct: the proof is constant size, and verifying it depends only on the size of statement, not the circuit and witness. It also achieves quasilinear overhead, through the use of FFT-based optimizations.
So, use it to study how SNARKs can be implemented, and to check your understanding of the accompanying tutorial As a project, consider extending this library to implement additional optimizations or protocol variants. This may also be useful in development for prototyping and reference implementations.
- babysnark.py: a succinct SNARK for square span programs
- babysnark_opt.py: improves on babysnark by using FFT optimizations, achieving quasilinear compute overhead
- finitefield/: a generic library for finite fields, and polynomials defined over them This library is adapted from posts by Jeremy Kun. See A Programmer's Introudction to Mathematics and Programming with Finite Fields
- polynomial_evalrep.py: -- an alternative polynomial abstraction, using evaluation at roots of unity, rather than coefficients.
{babysnark,babysnark_opt,polynomial_evalrep}.ipynb: the files are rendered in jupyter notebook form so they're more informative on github
This uses Python3. There are a few python dependencies, mainly numpy and py_ecc, an implementation of pairing cryptography including bls12-381.
pip install -r requirements.txt
To run:
python babysnark.py
python babysnark_opt.py
To rebuild the jupyter notebooks:
py2nb babysnark.py
py2nb babysnark_opt.py
py2nb polynomial_evalrep.py
