Reference implementation for the Poseidon Hashing algorithm.
Starkad and Poseidon: New Hash Functions for Zero Knowledge Proof Systems
This repository has been created so there's a unique library that holds the tools & functions required to perform Poseidon Hashes.
This hashes heavily rely on the Hades permutation, which is one of the key parts that Poseidon needs in order to work. This library uses the reference implementation of Dusk-Hades which has been designed & build by the Dusk-Network team.
The library provides the two hashing techniques of Poseidon:
The Sponge techniqe in Poseidon allows to hash an unlimited ammount of data
into a single Scalar.
The sponge hash techniqe requires a padding to be applied before the data can
be hashed.
This is done to avoid hash collitions as stated in the paper of the Poseidon Hash
algorithm. See: https://eprint.iacr.org/2019/458.pdf.
The inputs of the sponge_hash are always Scalar or need to be capable of being represented
as it.
The module provides two sponge hash implementations:
Sponge hash using Scalar as backend. Which hashes the inputed Scalars and returns a single
Scalar.
Sponge hash gadget using dusk_plonk::Variable as a backend. This techniqe is used/required
when you want to proof pre-images of unconstrained data inside of Zero-Knowledge PLONK circuits.
The Merkle Level Hashing is a technique that Poseidon is optimized-by-design
to perform.
This technique allows us to perform hashes of an entire Merkle Tree using
Dusk-Hades as backend.
The technique requires the computation of a bitflags element which is always
positioned as the first item of the level when we hash it, and it basically generated
in respect of the presence or absence of a leaf in the tree level.
This allows to prevent hashing collitions.
At the moment, this library is designed and optimized to work only with trees of ARITY
up to 4. That means that trees with a bigger ARITY SHOULD NEVER be used with this lib.
The module contains the implementation of 4 variants of the same algorithm to support the
majority of the configurations that the user may need:
Scalar backend for hashing Merkle Tree levels outside of ZK-Circuits whith two variants: One of them computes the bitflags item while the other assumes that it has already been computed and placed in the first Level position.
dusk_plonk::Variable backend for hashing Merkle Tree levels inside of ZK-Circuits,
specifically, PLONK circuits. This implementation comes also whith two variants;
One of them computes the bitflags item while the other assumes that it has already been
computed and placed in the first Level position.
```no_run
{
use anyhow::Result; use canonical::Canon; use canonicalderive::Canon; use canonicalhost::MemStore; use duskplonk::prelude::*; use duskposeidon::tree::{PoseidonAnnotation, PoseidonLeaf, PoseidonTree, merkle_opening};
// Constant depth of the merkle tree const DEPTH: usize = 17;
// Leaf representation
struct DataLeaf { data: BlsScalar, pos: u64, }
// Example helper
impl From
// Any leaf of the poseidon tree must implement PoseidonLeaf
impl PoseidonLeaf
// Position on the tree
fn pos(&self) -> u64 {
self.pos
}
// Method used to set the position on the tree after the `PoseidonTree::push` call
fn set_pos(&mut self, pos: u64) {
self.pos = pos;
}
}
fn main() -> Result<()> { // Create the ZK keys let pubparams = PublicParameters::setup(1 << 15, &mut rand::threadrng())?; let (ck, ok) = pub_params.trim(1 << 15)?;
// Instantiate a new tree with the MemStore implementation
let mut tree: PoseidonTree<DataLeaf, PoseidonAnnotation, MemStore, DEPTH> =
PoseidonTree::new();
// Append 1024 elements to the tree
for i in 0..1024 {
let l = DataLeaf::from(i as u64);
tree.push(l).unwrap();
}
// Create a merkle opening tester gadget
let gadget_tester =
|composer: &mut StandardComposer,
tree: &PoseidonTree<DataLeaf, PoseidonAnnotation, MemStore, DEPTH>,
n: usize| {
let branch = tree.branch(n).unwrap().unwrap();
let root = tree.root().unwrap();
let root_p = merkle_opening::<DEPTH>(composer, &branch);
composer.constrain_to_constant(root_p, BlsScalar::zero(), Some(-root));
};
// Define the transcript initializer for the ZK backend
let label = b"opening_gadget";
let pos = 0;
// Create a merkle opening ZK proof
let mut prover = Prover::new(label);
gadget_tester(prover.mut_cs(), &tree, pos);
prover.preprocess(&ck)?;
let proof = prover.prove(&ck)?;
// Verify the merkle opening proof
let mut verifier = Verifier::new(label);
gadget_tester(verifier.mut_cs(), &tree, pos);
verifier.preprocess(&ck)?;
let pi = verifier.mut_cs().construct_dense_pi_vec();
verifier.verify(&proof, &ok, &pi).unwrap();
Ok(())
}
} ```
The canonical implementations aim to make available a single representation of the Merkle tree to constrained (referred to as "hosted") and unconstrained (referred to as "host") environments.
For that, we rely on the features canon and canon_host.
canon feature will require all the crates needed for the Merkle tree to function.
canon_host feature will require canon, with the addition of the host environment implementations.
This crate contains info about all of the functions that the library provides as well as the documentation regarding the data structures that it exports. To check it, please feel free to go to the documentation page
This code is licensed under Mozilla Public License Version 2.0 (MPL-2.0). Please see LICENSE for further info.
Implementation designed by the dusk team.