Data Availability

A technique where light nodes randomly sample small chunks of a block's data to probabilistically verify its availability without downloading the entire block. This enables trust-minimized scaling by allowing nodes with limited resources to participate in DA verification.

• Key Innovation: Enables statistical security; the probability of a malicious block going undetected decreases exponentially with more samples.
• Example: Celestia pioneered this approach, allowing nodes to verify large data blocks with minimal bandwidth.

A data redundancy method that expands the original data with parity chunks, allowing the full dataset to be reconstructed even if a significant portion of the chunks are missing or withheld.

• Purpose: Protects against data withholding attacks. An attacker must hide a large, randomly distributed fraction of the data to succeed.
• Mechanism: Turns k chunks of data into n chunks (where n > k). The original data can be recovered from any k chunks.

A trusted, permissioned set of entities that sign attestations confirming they have received and stored the data for a block. This provides a lighter-trust alternative to full consensus-layer DA.

• Trade-off: Offers higher throughput and lower cost than on-chain DA but introduces a trust assumption in the committee's honesty and liveness.
• Use Case: Commonly used in optimistic and validium rollups (e.g., early versions of StarkEx) to reduce transaction costs.

Cryptographic commitments (like Merkle roots or KZG polynomial commitments) that allow anyone to verify that a specific piece of data is part of a larger published dataset without needing the entire dataset.

• Function: Provides a compact, verifiable fingerprint of the data. Fraud proofs or validity proofs can reference these commitments to challenge invalid state transitions.
• Core Component: Essential for all L2 rollups, which post these commitments to their L1 settlement layer.

The process by which full nodes or light clients using DAS collaborate to reconstruct an entire block from the available data chunks distributed across the peer-to-peer network.

• Fallback Mechanism: If sampling reveals data is available, but a node needs the full block, it requests the missing chunks from multiple peers.
• Network Resilience: Ensures the system can tolerate nodes going offline, as data is redundantly stored across the network.

Specialized blockchains or networks whose primary purpose is to order, broadcast, and guarantee the availability of transaction data for other execution layers (like rollups).

• Separation of Concerns: Decouples data publication from consensus and execution, optimizing each layer.
• Examples: Celestia is a modular DA layer. EigenDA is a restaking-based AVS on Ethereum. Ethereum's own consensus layer acts as the DA layer for its rollups.

A technique that allows light nodes to probabilistically verify data availability without downloading an entire block. By randomly sampling small chunks of data, nodes can achieve high confidence that the full data is available. This is a core innovation enabling scalable blockchains and light client security.

• How it works: A node requests multiple random pieces of the erasure-coded data.
• Key property: If any data is withheld, there is a high probability a sample will be missing.
• Example: Used by Celestia and Ethereum's danksharding roadmap.

A trusted, permissioned set of entities that sign attestations confirming data is available. This is a simpler, non-cryptoeconomic alternative to full DA layers, often used by Layer 2 rollups.

• Function: Committee members store data and provide cryptographic proofs of custody.
• Trust Assumption: Relies on the honesty of a majority of committee members.
• Use Case: Early versions of Arbitrum Nova and StarkEx (with Volition) use DACs for cost-efficient data availability.

A critical data redundancy technique used by DA layers to make sampling possible. Original data is expanded into a larger set of encoded pieces, so the original can be reconstructed from any subset of those pieces.

• Purpose: Guarantees data is recoverable even if a significant portion (e.g., 50%) is lost or withheld.
• 2D Reed-Solomon: A common scheme used in systems like Celestia and EigenDA, which arranges data in a matrix for efficient sampling.
• Requirement: Enables the security guarantees of Data Availability Sampling.

An Ethereum upgrade introducing a new transaction type that carries large, temporary data 'blobs' specifically for rollup data. Blobs are stored off the execution layer but guaranteed available by consensus for ~18 days.

• Mechanism: Blobs are posted to the Beacon Chain and subject to data availability sampling by consensus validators.
• Benefit: Provides cheap, high-volume DA for rollups, reducing L2 transaction costs significantly.
• Ecosystem Impact: The foundational step in Ethereum's danksharding roadmap, used by all major L2s.

Specialized blockchains whose primary function is to provide data availability as a service to other execution layers (like rollups). They decouple DA from execution and consensus.

• Core Proposition: Offer scalable, cost-optimized DA through dedicated networks.
• Examples: Celestia (first modular DA network), EigenDA (restaked AVS on EigenLayer), Avail.
• Architecture: Rollups post their transaction data to these layers, which use DAS and erasure coding to secure it.

A cryptographic mechanism that forces a node to prove it is actually storing the data it claims to have. It prevents validators from attesting to data availability without having the underlying data.

• Purpose: Secures Data Availability Sampling and committee-based systems against lazy validation.
• Implementation: A validator generates a proof derived from a secret key and the specific data, demonstrating possession.
• Ethereum's Plan: Integral to the full danksharding implementation to protect against data withholding attacks.

The core challenge of ensuring that block producers (e.g., validators, sequencers) have actually published all transaction data, allowing nodes to independently verify state transitions. If data is withheld, nodes cannot detect invalid transactions, leading to potential fraud proofs being impossible to construct. This is a fundamental scaling constraint addressed by Data Availability Sampling (DAS) and dedicated Data Availability Layers.

A malicious block producer publishes a block header but withholds some transaction data. This prevents honest nodes from:

• Reconstructing the full state.
• Generating fraud proofs for invalid state transitions in optimistic rollups.
• Creating ZK validity proofs without the underlying data. This can freeze funds or enable theft if the system cannot force data publication.

A cryptographic technique where light nodes randomly sample small pieces of block data to probabilistically verify its availability with high confidence. Key components include:

• Erasure Coding: Redundant encoding of data so any 50% of the pieces can reconstruct the whole.
• KZG Commitments: Polynomial commitments used to prove a specific data chunk belongs to the encoded block. This allows scalable verification without downloading the entire block, as implemented by Celestia and EigenDA.

A trusted, permissioned set of entities that sign attestations confirming data is available. Used by some early layer-2 rollups as a simpler, non-cryptographic alternative to full DAS. Risks include:

• Trust Assumption: Relies on honest majority of committee members.
• Collusion Risk: Committee members could collectively withhold data.
• Censorship: The committee becomes a central point of control.

An Ethereum upgrade introducing blobs—large, temporary data packets attached to transactions for layer-2 rollups. Security considerations:

• Blob Gas Market: Separate fee market prevents L1 congestion from pricing out rollup data.
• Pruning: Blobs are deleted after ~18 days, shifting long-term storage responsibility to rollups and Data Availability Layers.
• Proof of Custody: Validators must prove they have stored blob data, enforced through slashing.

Mechanisms to financially penalize validators who fail to make data available. Examples:

• EigenDA: Operators face slashing of restaked ETH for provable data withholding.
• Celestia: Validators are slashed from their staked tokens for incorrect encoding or data withholding. The security model depends on the cost of attack exceeding potential profit, tying cryptoeconomic security directly to data integrity.