Coral

This is an implementation of Coral, a system for generating zero-knowledge proofs that a committed document matches is consistent with a public Context Free Grammar. The details of Coral are described in our paper: Coral: Fast Succinct Non-Interactive Zero-Knowledge CFG Proofs.

Compile

cargo build --release

With metrics:

cargo build --release --features metrics

With pipeined proving and witness generation:

cargo build --release --features para

Usage

Usage: coral [OPTIONS] <--commit|--prove|--verify|--e2e>

Options:
      --commit
      --prove
      --verify
      --e2e
      --cmt-name <FILE>     Optional name for .cmt file
      --proof-name <FILE>   Optional name for .proof file
  -d, --doc <FILE>
  -m, --metrics <FILE>      Metrics and other output information
  -g, --grammar <FILE>      .pest file containing the grammar
  -b, --batch-size <USIZE>  Batch size [default: 1]
  -h, --help                Print help
  -V, --version             Print version

Coral has the ability to process multiple nodes in the parse tree per folding, this is controlled by the --batch-size parameter. A larger batch size will require fewer total proving steps, but each step will have more constraints. In our experience, between 5 and 10 total steps is usually optimal. Depending on you tree this will be a batch size between 150 and 1,000. Performace will significantly degrade as the batch size increases beyond 2,500.

You can use --cmt-name and --proof-name to choose names for your commitment and proof files. This is optional - Coral will choose a name for the commitment/proof if you do not.

Perpetual Powers of Tau

You will need a local copy of the Perpetual Powers of Tau to run Coral. Coral is hardcoded to use *./ppot_0080_23.ptau. However, you can use whichever one you prefer by changing the specified file here and here.

Sample Grammars

The grammars directory contains sample grammars for a JSON, TOML, and a subset of C. You can run Coral for JSON with the following

./target/release/coral -d ./tests/test_docs/json/test_json_64.txt -g ./grammars/json.pest -b 100 -m ./tests/results/timings/scale/json_64_coral.txt --e2e

Reproducing Baseline Results

If you're interested in reproducing our baseline results, you can run the corresponding scripts in the tests/scripts directory. We have also provided a python notebook DataCleaning to help reproduce our analysis.

Thank you for using Coral, Happy proving!