RIPP (Rust Inner Pairing Products)

RIPP is a Rust library for proofs about inner pairing products, and applications built atop these. These protocols and applications are described in our paper "Proofs for Inner Pairing Products and Applications"

The library currently contains an implementation of our proof system for verifiably outsourcing pairing products. In the future, we intend to implement the other protocols described in our paper, along with the polynomial commitment schemes and our protocol for aggregating Groth16 proofs based upon these protocols.

This library is released under the MIT License and the Apache v2 License (see License).

WARNING: This is an academic proof-of-concept prototype, and in particular has not received careful code review. This implementation is NOT ready for production use.

Build guide

The library compiles on the stable toolchain of the Rust compiler. To install the latest version of Rust, first install rustup by following the instructions here, or via your platform's package manager. Once rustup is installed, install the Rust toolchain by invoking:

rustup install stable

After that, use cargo, the standard Rust build tool, to build the library:

git clone https://github.com/scipr-lab/ripp.git
cd ripp
cargo build --release

This library comes with unit tests for each of the provided crates. Run the tests with:

cargo test

Lastly, the library comes with benchmarks.

cargo bench
cargo run --release --example groth16_aggregation
cargo run --release --example scaling-ipp

License

RIPP is licensed under either of the following licenses, at your discretion.

• Apache License Version 2.0 (LICENSE-APACHE or http://www.apache.org/licenses/LICENSE-2.0)
• MIT license (LICENSE-MIT or http://opensource.org/licenses/MIT)

Unless you explicitly state otherwise, any contribution submitted for inclusion in RIPP by you shall be dual licensed as above (as defined in the Apache v2 License), without any additional terms or conditions.

Reference paper

Proofs for Inner Pairing Products and Applications
Benedikt Bünz, Mary Maller, Pratyush Mishra, Psi Vesely
IACR ePrint Report 2019/1177