Integrated, Efficient, and Extensible Zero-Knowledge Proof Engineering
You can install the library from PyPI using pip install:
pip install picozk
Or, clone the repository and then install with pip install (This library
requires Python3):
git clone git@github.com:uvm-plaid/picozk.git
cd picozk
pip install .
If you want to run the examples, you'll need to install
some extra Python packages (which are optional and are not required to
install the core library). These dependent packages can be done by
running the command pip install ".[examples]".
To generate a zero-knowledge (ZK) statement, write a Python program
that uses the PicoZK library, and then run the program to generate the
statement. For example, the following program corresponds to a ZK
statement that the prover knows a number x such that x + x * x is
30:
from picozk import *
with PicoZKCompiler('picozk_test'):
x = SecretInt(5)
z = x + x * x
assert0(z + -30)Running this program results in three files:
picozk_test.rel: the relation, which is the statement itself (known to both prover and verifier)picozk_test.type0.ins: the instance, which holds public information (known to both prover and verifier, always empty in our setting)picozk_test.type0.wit: the witness, which holds secret information (known only to prover)
These files can be used to generate a ZK proof using any backend compatible with the SIEVE intermediate representation (IR). There are currently two open-source backends compatible with the SIEVE IR:
PicoZK is made available under the MIT License.
DISTRIBUTION A: Approved for Public Release. Distribution is Unlimited. This material is based upon work supported by DARPA under Contract No. HR001120C0087 and by the Broad Agency Announcement Program and the Cold Regions Research and Engineering Laboratory (ERDC-CRREL) under Contract W913E521C0003. Any opinions, findings and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of DARPA or ERDC-CRREL.