🚀 Stoffel MPC Protocols

This repository provides a fully-asynchronous, robust collection of MPC (Multi-Party Computation) protocols designed to run inside the StoffelVM runtime and the StoffelNet networking layer. However, it can also be used independently.

The repository is designed as a general-purpose foundation for hosting multiple MPC protocol families that share common networking, preprocessing, and arithmetic components. This repository is intended to serve as a collection of MPC protocols, not a single fixed construction.

At present, HoneyBadgerMPC is the only fully integrated end-to-end MPC protocol. However, the architecture is deliberately modular so that additional MPC protocols can be added over time without rewriting core components.

Key design goals:

• Protocol-agnostic networking via the Network trait
• Reusable common sub-protocols (rbc,secret sharing,etc)
• Shared arithmetic layers (field, fixed-point, integer)
• Explicit protocol routing via compact SessionIds

HoneyBadgerMPC 🦡

It includes implementations for HoneyBadgerMPC like random sharing protocols, preprocessing, Beaver triples, fixed-point arithmetic, integer arithmetic, and robust reconstruction procedures.

The core engine is built around the HoneyBadgerMPCNode, which orchestrates all subprotocols using an asynchronous message-passing model.

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✨ Features

Included Protocols

Category	Protocol	Status
Preprocessing	Shamir Random Share (RanSha)	✔ Implemented
Preprocessing	Double Sharing / Random Double Sharing (DouSha / RanDouSha)	✔ Implemented
Preprocessing	Beaver Triple Generation	✔ Implemented
Preprocessing	Random Bit / PRandBit / PRandInt	✔ Implemented
Arithmetic	Secure Beaver Multiplication	✔ Implemented
Arithmetic	Fixed-Point Mul / DivWithConst / Trunc	✔ Implemented
I/O	Distributed Input / Output (via RBC)	✔ Implemented
Reconstruction	Robust Interpolation	✔ Implemented
Reconstruction	Batch Reconstruction	✔ Implemented
Complete MPC	HoneyBadgerMPC Core	✔ Implemented

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📦 Crate Structure

mod.rs exposes the following modules:

robust_interpolate/       # RS-based robust interpolation (HBMPC Fig.1)
batch_recon/              # Batch reconstruction (HBMPC Fig.2)
ran_dou_sha/              # Random double sharing (HBMPC Fig.3)
share_gen/                # Random share generation
double_share/             # Basic double-share generation
triple_gen/               # Beaver triple generator
fpmul/                    # Fixed-point arithmetic protocols
input/, output/           # MPC I/O protocols via RBC
mul/                      # Secure Beaver multiplication
preprocessing/            # Preprocessing store management
share_gen/                # Random Shamir share generation

All modules plug into:

HoneyBadgerMPCNode<F, R>

A node capable of:

• Running preprocessing (random shares, doubles, triples, PRandBit, PRandInt)
• Performing secure arithmetic operations
• Handling RBC-based input and output
• Routing messages using compact SessionId fields

⏱️ Offline Phase, Abort Semantics, and Timeouts

The offline (preprocessing) phase of HoneyBadgerMPC is intentionally designed to be non-robust. In line with the original HoneyBadgerMPC design, preprocessing protocols (e.g., random sharing, batch reconstruction, Beaver triple generation) are expected to abort on failure and be restarted by the caller until sufficient preprocessing material has been generated.

Typical failure conditions include:

• A node going offline
• Network message loss or delays
• RBC or subprotocols failing to terminate

⚠️ Important:
The preprocessing protocols do not internally enforce timeouts. If a required message or share never arrives, the protocol may wait indefinitely. As a result, timeout handling is the responsibility of the caller. Preprocessing should always be wrapped in external timeout logic, with retry or abort behavior defined by the application.

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🏃 How to Run

Running MPC requires:

1. Start N HoneyBadgerMPCNode instances
2. Connect them with a StoffelNet‐compatible network (Network trait)
3. Spawn a processing loop for each node
4. Send messages into the network
5. Call MPC operations like multiplication, fixed-point division, etc.

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▶ Minimal Example: Running a 4-Party Secure Multiplication

Replace FakeNetwork with any Network implementation (FakeNetwork, StoffelNet, etc.):

#[tokio::test]
async fn test_mul() {
    let n = 4;
    let t = 1;
    let mut rng = test_rng();

    // ---------------- Network ----------------
    let config = FakeNetworkConfig::new(500);
    let (network, receivers, _) = FakeNetwork::new(n, Some(vec![]), config);
    let network: Arc<FakeNetwork> = Arc::new(network);

    // ---------------- Inputs ----------------
    let x = Fr::rand(&mut rng);
    let y = Fr::rand(&mut rng);

    let xs = RobustShare::compute_shares(x, n, t, None, &mut rng).unwrap();
    let ys = RobustShare::compute_shares(y, n, t, None, &mut rng).unwrap();

    // ---------------- Nodes ----------------
   let nodes = create_global_nodes::<Fr, Avid, RobustShare<Fr>, FakeNetwork>(
        n, t, 2,   //No of beaver triples needed, 2 in this case for one multiplication
        111, //Instance-ID
    );

    // ---------------- Process messages ----------------
    receive::<Fr, Avid, RobustShare<Fr>, FakeNetwork>(receivers, nodes.clone(), network.clone());

    // ---------------- Run MPC ----------------
    let handles: Vec<_> = (0..n)
        .map(|pid| {
            let mut node = nodes[pid].clone();
            let net = network.clone();
            let x = vec![xs[pid].clone()];
            let y = vec![ys[pid].clone()];

            tokio::spawn(async move {
                let shares = node.mul(x, y, net).await.expect("mul failed");
                return shares[0].clone();
            })
        })
        .collect();

    let shares: Vec<_> = futures::future::join_all(handles)
        .await
        .into_iter()
        .map(|res| res.expect("task panicked"))
        .collect();

    // ---------------- Collect & Check ----------------

    let (_, z) = RobustShare::recover_secret(&shares[..=2 * t], n, t).unwrap();
    assert_eq!(z, x * y);
}


pub fn create_global_nodes<F: PrimeField, R: RBC + 'static, S, N>(
    n_parties: usize,
    t: usize,
    n_triples: usize,
    instance_id: u32,
) -> Vec<HoneyBadgerMPCNode<F, R>>
where
    N: Network + Send + Sync + 'static,
    S: SecretSharingScheme<F>,
    HoneyBadgerMPCNode<F, R>: MPCProtocol<F, S, N, MPCOpts = HoneyBadgerMPCNodeOpts>,
{
    let parameters =
        HoneyBadgerMPCNodeOpts::new(n_parties, t, n_triples, 0, instance_id, 0, 0, 0, 0).unwrap();
    (0..n_parties)
        .map(|id| HoneyBadgerMPCNode::setup(id, parameters.clone(), vec![]).unwrap())
        .collect()
}

pub fn receive<F, R, S, N>(
    mut receivers: Vec<Receiver<Vec<u8>>>,
    mut nodes: Vec<HoneyBadgerMPCNode<F, R>>,
    net: Arc<N>,
) where
    F: PrimeField,
    R: RBC + 'static,
    N: Network + Send + Sync + 'static,
    S: SecretSharingScheme<F>,
    HoneyBadgerMPCNode<F, R>: MPCProtocol<F, S, N>,
{
    assert_eq!(
        receivers.len(),
        nodes.len(),
        "Each node must have a receiver"
    );

    for i in 0..receivers.len() {
        let mut rx = receivers.remove(0);
        let mut node = nodes.remove(0);
        let net_clone = net.clone();

        tokio::spawn(async move {
            while let Some(raw_msg) = rx.recv().await {
                if let Err(e) = node.process(raw_msg, net_clone.clone()).await {
                    tracing::error!("Node {i} failed to process message: {e:?}");
                }
            }
            tracing::info!("Receiver task for node {i} ended");
        });
    }
}

For more examples check out the tests.

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🧪 Running Tests

Run everything:

cargo test

Run a specific test:

cargo test test_session_id

See logs:

RUST_LOG=info cargo test -- --nocapture

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🔌 Running Preprocessing

let mut rng = StdRng::from_entropy();
node.run_preprocessing(net.clone(), &mut rng).await?;

This generates:

• Random Shamir shares
• Double shares
• Random double shares
• Beaver triples
• PRandBit outputs
• PRandInt outputs

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📚 Reference Papers

• HoneyBadgerMPC — https://eprint.iacr.org/2019/883
• Fixed-Point Secure Computation — https://ifca.ai/pub/fc10/31_47.pdf