Data Availability Committee (DAC)

The DAC's primary function is to provide cryptographic attestations that specific data (e.g., transaction batches) is available for download. Each member independently signs a commitment to the data, creating a multi-signature attestation. This proof is posted to the parent chain (e.g., Ethereum), allowing users and verifiers to trust that the data exists without downloading it themselves, a concept known as data availability sampling via proxy.

DACs store the full transaction data off-chain, typically on high-availability, redundant storage systems. This is the core scaling benefit: only small data commitments and attestations are posted to the costly Layer 1. The data is made available via peer-to-peer networks or dedicated content-addressable storage (like IPFS or custom servers). Users can reconstruct the chain state by fetching this data using the attested hashes.

A DAC operates on an explicit trust assumption, distinct from the cryptographic security of the base layer. Security requires that a supermajority (e.g., 5 of 7) of committee members are honest and available. This is a weaker security model compared to full on-chain data availability but stronger than a single operator. The threat model involves data withholding attacks, where malicious members could collude to withhold data, preventing state verification.

DAC members are typically known, reputable entities (e.g., foundations, exchanges, staking providers) selected by the L2 project. Their role is often stake-based or reputation-based. Incentives can include:

• Protocol fees for providing attestations.
• Slashing conditions or reputation loss for non-performance or malicious behavior.
• The economic incentive to maintain the health and usability of the L2 network they support.

DACs are commonly used with Optimistic Rollups. When a fraud proof is challenged, the verifier needs the specific data to compute the correct state. The DAC's attestation guarantees this data is retrievable. In Zero-Knowledge Rollups (zk-Rollups), validity proofs ensure state correctness, but a DAC can still be used to ensure data is available for user bridging and transparency, complementing the proof.

This contrasts with Data Availability Sampling (DAS) used in validiums and zk-rollups with off-chain data. DAS allows light nodes to probabilistically verify data availability without trust by sampling small, random pieces. A DAC provides deterministic, attestation-based availability with known trust assumptions. DAS is more decentralized and trust-minimized but requires a robust peer-to-peer network; a DAC offers simpler implementation and potentially higher throughput with defined trust.

A DAC introduces a trusted third-party assumption. Users must trust that a supermajority of committee members is honest and will not collude to withhold data. This is a weaker security model than cryptoeconomic security, where validators are financially penalized (slashed) for misbehavior. The system's liveness depends on the committee's continued cooperation.

The primary risk is a data withholding attack, where malicious committee members refuse to provide the data needed to reconstruct the chain's state. This can lead to:

• Invalid state transitions going unchallenged.
• Funds becoming frozen if users cannot generate fraud proofs.
• A security failure equivalent to the committee's corruption threshold (e.g., 4 of 7 members).

Security depends heavily on committee composition and incentives. Key considerations include:

• Member Identity: Are they known, reputable entities (e.g., exchanges, foundations) or permissionless?
• Economic Bonding: Are members required to post staking bonds that can be slashed for malfeasance?
• Rotation & Governance: How are members added or removed? Centralized governance poses a single point of failure.

DACs are often contrasted with Data Availability Sampling (DAS) used by data availability layers like Celestia or Ethereum's danksharding. DAS allows light clients to probabilistically verify data availability without trusting a specific committee, offering stronger cryptographic guarantees and permissionless participation. DACs are a pragmatic solution for early-stage networks prioritizing speed to market.

The role of DACs is evolving within modular stacks. They can act as a hybrid or fallback layer. For example, a system might primarily use a decentralized DA layer but employ a DAC for rapid finality in failure scenarios. The long-term trend is toward eliminating the trust assumption via cryptographic proofs (Validity Proofs) and scalable data availability layers, moving from committee-based to cryptography-based security.

A cryptoeconomic mechanism that allows light nodes to probabilistically verify data availability without downloading an entire block. Key aspects include:

• Random Sampling: Nodes request small, random chunks of data.
• Statistical Security: The probability of accepting unavailable data decreases exponentially with more samples.
• Foundation for Scaling: This is the core innovation enabling Ethereum's danksharding and secure, high-throughput rollups.

A specialized blockchain or network whose primary function is to guarantee that transaction data is published and stored for a verifiable period. This decouples execution from data availability. Examples include:

• Celestia: A modular network acting as a pluggable DA layer.
• EigenDA: A restaking-secured AVS (Actively Validated Service) on EigenLayer.
• Ethereum Blobs: A dedicated data space (blob-carrying transactions) introduced by EIP-4844.

These are the two security models for optimistic and zk-rollups, both critically dependent on data availability.

• Validity Proofs (ZK-Rollups): Provide cryptographic proof of correct state transition. DA is required to reconstruct state and for data compression.
• Fraud Proofs (Optimistic Rollups): Assume correctness but allow challenges. DA is essential for verifiers to detect and prove fraud. Without available data, fraud proofs are impossible.

A data redundancy technique fundamental to data availability schemes. It expands the original data with parity chunks.

• Process: Data is encoded so the original can be reconstructed from only a subset of the total chunks.
• Purpose: Makes data availability fault-tolerant. Light clients using Data Availability Sampling can detect if even a single chunk is missing from the expanded data.

A permissioned set of entities tasked with attesting that transaction data for a rollup is available. This is a trusted but simpler alternative to decentralized DA layers.

• Operation: Members cryptographically sign attestations.
• Use Case: Common in early Layer 2 implementations (e.g., early Arbitrum Nova) to reduce costs before mature decentralized DA.
• Trust Assumption: Relies on the honesty of a majority of committee members.

An Ethereum upgrade that created a separate, low-cost data space for rollups, known as blobs.

• Key Innovation: Blobs are large data packets (~128 KB each) stored by consensus nodes for ~18 days, separate from calldata.
• Purpose: Drastically reduces DA costs for L2s while keeping Ethereum as the secure DA layer.
• Proto-Danksharding: This is the first step towards full danksharding, which will incorporate Data Availability Sampling.