Setting Up a Validium for Private, Scalable Settlements

A Validium is a specific type of zero-knowledge rollup (zk-rollup). Like all zk-rollups, it batches thousands of transactions off-chain and submits a cryptographic validity proof (a zk-SNARK or zk-STARK) to the underlying Layer 1 blockchain, typically Ethereum. This proof verifies the integrity of all transactions in the batch without revealing their details. The critical architectural difference lies in data availability: while standard zk-rollups post transaction data on-chain as calldata, Validiums keep this data off-chain with a committee of data availability managers. This trade-off drastically reduces gas costs and increases privacy but introduces a different trust assumption regarding data access.

For payment settlements, this architecture offers distinct advantages. Throughput can reach over 9,000 transactions per second (TPS), as the bottleneck shifts from L1 block space to the prover's computational capacity. Costs are minimized because only the tiny proof and minimal state updates are published on-chain. Crucially, privacy is enhanced; sensitive payment details like amounts and counterparties remain off-chain, visible only to the data availability committee and the transacting parties. This makes Validium suitable for institutional settlements, payroll, and B2B transactions where data confidentiality is required.

Setting up a Validium network requires several core components. You need a Sequencer to order transactions, a Prover to generate validity proofs (using frameworks like zkSync's ZK Stack or StarkWare's StarkEx), and a Data Availability Committee (DAC). The DAC, a set of known, permissioned nodes, holds the transaction data and attests to its availability. A smart contract on Ethereum, the Verifier Contract, receives proofs and state updates from the prover and checks the DAC's signatures to ensure data is available before finalizing the batch.

Here is a simplified conceptual flow for a payment transaction: 1. A user submits a private payment to the Sequencer. 2. The Sequencer orders it into a batch with other transactions. 3. The Prover computes a zk-proof for the entire batch. 4. The DAC members sign a message confirming they hold the batch's data. 5. The Verifier Contract on L1 checks the proof and the DAC signatures, then updates the Merkle root of accounts. The user's balance is updated off-chain based on the new state root. The entire process, except for the proof and signatures, remains off-chain.

When implementing, key decisions involve choosing the proving system and DAC structure. zk-SNARKs offer smaller proof sizes but require a trusted setup, while zk-STARKs are trustless but generate larger proofs. The DAC can be operated by the entity running the Validium, a consortium of partners, or a decentralized set of staked nodes. Security hinges on the DAC's honesty; if it withholds data, users cannot withdraw funds, though fraud proofs are not needed for invalid state transitions (prevented by the validity proof). Projects like StarkEx (powering dYdX and Immutable X) offer a battle-tested framework for deploying a Validium.

In summary, Validium architecture provides a powerful template for building high-performance private payment rails. Its off-chain data model is the key to achieving scalability and confidentiality, making it a compelling choice for enterprises and financial institutions looking to leverage blockchain settlement without exposing sensitive data or incurring prohibitive Ethereum gas fees. Development is accelerating with SDKs and modular stacks, lowering the barrier to deploying a custom settlement layer.

Deploying a Validium requires a foundational understanding of zero-knowledge proofs (ZKPs) and data availability. A Validium is a ZK-rollup that settles proofs on a base layer like Ethereum, but stores transaction data off-chain. This architecture provides scalability and privacy, as transaction details are not published on-chain. Key prerequisites include familiarity with Ethereum's Layer 1, smart contract development, and the core trade-off: enhanced throughput and privacy come with the requirement to trust a committee or a proof-of-stake network for data availability, unlike a standard ZK-rollup.

Your development environment must support the tooling for ZK circuit development and proof generation. This typically involves setting up Rust and Cargo for frameworks like StarkWare's Cairo or zkSync's zkEVM toolchain. You will also need a Node.js environment and package managers like npm or yarn for interacting with the network. Essential software includes Docker for containerized services and Git for version control. A solid grasp of cryptographic primitives, such as elliptic curve operations and hash functions, is necessary for understanding the underlying proof systems.

The core system requirement is access to a data availability committee (DAC) or a decentralized data availability layer like EigenDA or Celestia. You must configure the network of nodes that will store and attest to the availability of transaction data. Furthermore, you need to deploy a set of verifier smart contracts on your chosen settlement layer (e.g., Ethereum Mainnet, Arbitrum, or Polygon). These contracts will verify the ZK validity proofs submitted by your sequencer. Operational requirements include a sequencer node to batch transactions and generate proofs, and a prover machine with significant CPU and RAM for computationally intensive proof generation.

A Data Availability Committee (DAC) is a set of trusted, permissioned nodes responsible for storing and attesting to the availability of transaction data off-chain. Unlike a zkRollup, where data is posted to a base layer like Ethereum L1, a Validium keeps data with the DAC. This removes the L1 data publishing cost and bottleneck, enabling higher throughput and lower fees, but introduces a trust assumption: users must trust that a majority of the DAC members are honest and will provide the data upon request. The DAC's primary job is to collectively sign cryptographic attestations, often using BLS signatures, that confirm the data for a specific state transition is available and can be reconstructed.

To configure a DAC, you must first define its members and the consensus mechanism. A typical setup involves 5 to 20 known entities, such as reputable exchanges, foundations, or institutional validators. Each member runs a DAC node, which includes a sequencer client for receiving batches, a secure storage layer (like a decentralized storage network or private cloud), and a signing service. The consensus is usually a simple majority (e.g., 2/3 or 3/4) required to sign a data attestation. You can use a framework like StarkEx's DAC software or build a custom solution using libraries for BLS threshold signatures, such as the gnark-crypto library in Go.

The technical configuration begins with generating the committee's cryptographic keys. A common pattern uses a Distributed Key Generation (DKG) ceremony to create a shared BLS public key and individual private key shares for each member. No single member holds the full private key, enhancing security. The public key is registered on-chain, often in the Validium's smart contract on L1, so users and the verifier contract can validate attestations. The DAC members must also agree on and configure the data storage backend, ensuring it provides high availability and redundancy—options include IPFS clusters, Arweave, or private AWS S3 buckets with strict access policies.

Here is a simplified example of how a DAC attestation might be structured and verified in a smart contract. The sequencer sends a batch's data hash to the DAC members, who sign it with their BLS key shares. An aggregator combines the signatures into a single attestation.

solidityCopy
// Pseudocode for attestation verification in an L1 contract
function verifyDAAttestation(
    bytes32 batchDataHash,
    uint256 batchNumber,
    bytes calldata aggregatedSignature
) public view returns (bool) {
    // Reconstruct the signed message from the batch details
    bytes32 message = keccak256(abi.encodePacked(batchDataHash, batchNumber));
    // Verify the BLS signature against the committee's public key
    return BLSAggregatedSignature.verify(
        committeePublicKey,
        message,
        aggregatedSignature
    );
}

This check ensures the attested data exists off-chain before the new state root is accepted on-chain.

Finally, you must establish the operational protocols for the DAC. This includes defining the SLA for data availability, the process for members to join or exit (which requires a key reshare), and the emergency data release mechanism. A data availability challenge system should be implemented, allowing users to request data directly from the committee. If a user cannot retrieve their data, they can submit a challenge on-chain, forcing the DAC to provide a proof of availability or face slashing of their bonded stake. This setup phase is critical, as the security and liveness of the entire Validium chain depend on the DAC's correct and honest operation.

A zk-SNARK circuit is a program written in a specialized language like Circom or Noir. It doesn't execute transactions; instead, it defines the constraints that a valid private payment must satisfy. For a basic payment, the circuit takes private inputs (the sender's secret key and amount) and public inputs (the transaction hash and new state root). It proves, without revealing the secrets, that: the sender owns the funds, the balance is sufficient, and the new Merkle root correctly reflects the updated balances.

The circuit's primary job is to generate a witness—a set of values that satisfy all constraints—and a corresponding proof. For example, using the Circom library circomlib, you would implement a component like LessThan to ensure the spent amount does not exceed the balance. The circuit also hashes the new state commitments. A critical constraint validates the sender's knowledge of the private key corresponding to the public key in the Merkle tree, typically using a MiMC or Poseidon hash function for efficient ZK-friendly hashing.

Here is a simplified conceptual structure for a payment circuit in pseudocode:

codeCopy
// Private Inputs: secretKey, balance, amount, merklePath
// Public Inputs: rootBefore, rootAfter, txHash

signal output validProof;

// 1. Verify sender owns the account
computedPublicKey = MiMC(secretKey);
assert(computedPublicKey == leafInMerkleTree);

// 2. Verify sufficient balance
assert(balance >= amount);
newBalance = balance - amount;

// 3. Compute and verify the new Merkle root
newLeaf = hash(newBalance, computedPublicKey);
calculatedRoot = merkleRoot(newLeaf, merklePath);
assert(calculatedRoot == rootAfter);

validProof <== 1;

This logic ensures the proof is only valid if all financial and cryptographic conditions are met.

After defining the circuit, you compile it into an R1CS (Rank-1 Constraint System) and a wasm file for witness generation. This compilation step, using circom CLI, transforms your high-level logic into the arithmetic constraints that the prover will satisfy. You then perform a trusted setup (Phase 2 ceremony) for this specific circuit to generate the proving and verification keys (pk.zkey and vk.json). These keys are essential; the prover uses pk.zkey to create proofs, and the on-chain verifier contract uses vk.json to verify them.

Design considerations directly impact performance and cost. The number of constraints influences proving time and gas fees for verification. Using ZK-friendly cryptographic primitives is essential; standard SHA-256 is computationally expensive in a circuit, whereas Poseidon hash is designed for this environment. Furthermore, the circuit must be designed to interface with your chosen Data Availability solution, as the public inputs (like the new state root) will be posted off-chain, and their availability must be verifiable.

Finally, rigorous testing is non-negotiable. Use test frameworks like Mocha with Chai for Circom, or native tests in Noir, to simulate a wide range of scenarios: valid payments, insufficient balance attempts, and invalid Merkle proofs. The circuit is the foundation of your Validium's security—its correct implementation ensures that only valid state transitions can be proven, maintaining the integrity of the entire system without revealing sensitive user data.

The on-chain verifier contract is the final arbiter of state transitions for your Validium. Unlike a zkRollup, which posts state data on-chain, a Validium only posts a validity proof and the new state root. This contract's sole job is to verify the cryptographic proof generated by your prover (Step 2) and, if valid, update the official state root stored on the L1 (like Ethereum Mainnet). Deploying this contract establishes the canonical source of truth for your chain's state, enabling secure withdrawals and trustless bridging.

You will typically deploy a pre-compiled verifier contract provided by your chosen zk-proof framework, such as PlonkVerifier.sol from snarkjs or a Verifier contract generated by Circom. The deployment process is straightforward but critical. Using Foundry or Hardhat, you will compile and deploy the contract to your target L1 network. For a test deployment, use a testnet like Sepolia. The key output is the contract's deployed address, which you must configure in your node software (Step 4).

Here is a simplified example of a Foundry script to deploy a verifier:

bashCopy
// DeployVerifier.s.sol
import "forge-std/Script.sol";
import "../src/PlonkVerifier.sol";

contract DeployScript is Script {
    function run() external {
        vm.startBroadcast();
        PlonkVerifier verifier = new PlonkVerifier();
        console.log("Verifier address:", address(verifier));
        vm.stopBroadcast();
    }
}

Run it with forge script script/DeployVerifier.s.sol --rpc-url $SEPOLIA_RPC --broadcast. Ensure you fund the deployer address with test ETH.

After deployment, you must verify the contract source code on a block explorer like Etherscan. This is a non-negotiable step for transparency and security, allowing anyone to audit the verification logic. Once verified, the contract is immutable and ready to receive proofs. The core function users and your sequencer will call is verifyProof(proof, publicInputs), which returns true for a valid proof. This function call is the settlement event that updates the L1 state root.

The gas cost of the verifyProof function is your primary ongoing L1 expense. For a Plonk proof, verification typically costs 200k-400k gas, while Groth16 can be as low as 150k gas. Optimizing this is crucial for cost-effective operation. Some frameworks offer batch verifiers for multiple proofs. Remember, this contract contains no business logic—it is a pure, stateless verifier. All application logic and state data remain off-chain in your Validium's dedicated environment.

With the verifier live on the L1, your Validium's security model is now active. The L1 contract guarantees that only proven-correct state roots are accepted. The next step is to configure your node (sequencer and prover) to submit proofs to this contract address after processing batches of transactions. This completes the core trustless loop: compute off-chain, prove correctness, verify on-chain.

The operator node is the central coordinator of your Validium network. Its primary responsibilities are to sequence transactions into batches, execute them to compute new state roots, and generate a zero-knowledge proof (ZKP)—specifically a STARK or SNARK—that attests to the correctness of this state transition. This proof is then posted to the parent chain (e.g., Ethereum) as a compact validity certificate. You will typically build this component by forking and customizing an existing rollup framework like Polygon CDK, StarkEx, or zkSync's ZK Stack, which provide the foundational proving system and node architecture.

Your development focus will be on configuring the node's sequencer logic and state management. This involves setting rules for transaction ordering (often first-come-first-served for simplicity), managing the mempool, and defining how the node interacts with the data availability layer. You must implement the logic for constructing batch payloads and submitting the resulting state root and proof to the RollupContract on L1. The node must also maintain a synchronized copy of the chain's state (a Merkle tree) and update it with each proven batch.

A critical integration is with the chosen proving system. For a STARK-based stack like Polygon CDK, the node will call a STARK prover service (e.g., a prover-client) with the batch data to generate a proof. Your code must handle this RPC call, manage proving jobs, and post the proof to chain. The architecture often separates the sequencer node from the prover node for scalability, meaning your operator software may need to coordinate between these services. Ensure your implementation includes robust error handling for failed proof generation or L1 submission.

Finally, the operator must be configured for the data availability (DA) solution. For a Validium, this is not Ethereum calldata. You will integrate with your chosen DA layer (e.g., Celestia, EigenDA, or a DAC) by implementing its specific APIs. After proving a batch, your node must post the corresponding transaction data to the DA layer and include only the data availability attestation (like a data root hash or signature) in the L1 transaction. The node software must also be able to fetch this data when serving state proofs for user withdrawals.

Your local Validium node is now operational, using a Data Availability Committee (DAC) and a zero-knowledge proof system like zk-SNARKs or zk-STARKs to batch and prove transactions off-chain. The key components you've deployed include the sequencer for ordering transactions, the prover for generating validity proofs, and the smart contracts on the base layer (e.g., Ethereum) for proof verification and state root updates. This architecture provides significant scalability—potentially over 10,000 TPS—while keeping all transaction data private, a critical feature for enterprise and institutional use cases.

To move towards a production environment, several critical steps remain. First, decentralize your DAC by onboarding multiple, independent operators running the node software you just configured, ensuring no single entity controls the data. Second, implement a robust watchtower service to monitor the base layer contract and DAC for liveness, safeguarding user funds. Third, thoroughly audit your custom bridge contracts and the cryptographic circuits used by your prover. Finally, consider integrating with established zkEVM rollup frameworks like Polygon zkEVM CDK or Starknet's Madara for a more battle-tested stack, rather than building all components from scratch.

The next phase involves developer tooling and ecosystem growth. Explore SDKs and APIs for easier dApp integration, such as the Starknet.js library for StarkEx-based Validiums or Polygon's zkEVM tools. Monitor the evolving landscape of EigenDA and Celestia for alternative, potentially more decentralized data availability solutions that could replace your DAC. For continued learning, review the official documentation for StarkEx, Polygon zkEVM, and the Ethereum Rollup-centric roadmap. Your Validium setup is a powerful foundation for building scalable, private applications on Ethereum.