Data Hash

Projects use Merkle roots (the hash of all data hashes in a set) to commit to large datasets on-chain efficiently. Users can then provide a Merkle proof to verify a single piece of data's inclusion without needing the entire dataset.

• ReFi Example: A carbon credit registry stores the hash of its entire ledger on-chain. A verifier can cryptographically prove a specific credit's existence and attributes using a compact proof derived from the root hash.

A commit-reveal scheme uses hashing to hide information during a voting or bidding process while preventing later alteration. Participants first submit the hash of their choice (the commit). Later, they reveal the original data, which can be verified against the earlier hash.

• Web3 Use Case: Used in DAO governance for private voting or in NFT auctions to prevent bid sniping, ensuring fairness and secrecy.

Blockchain blocks contain a block header hash and a state root hash. The state root is a Merkle-Patricia Trie root hash representing the entire network state (account balances, contract storage). Light clients can efficiently verify transaction inclusion and account states by checking hashes against this root.

• Core Function: Enables trustless verification without running a full node.

NFT metadata and provenance trails are secured with hashes. The tokenURI in an NFT contract often points to a JSON file hosted on IPFS, identified by its hash. Any change to the metadata changes the hash, breaking the link and proving tampering.

• Application: Used in digital art, supply chain ReFi, and verifiable credentials to create an immutable audit trail of an asset's history and attributes.

Smart contracts and decentralized applications (dApps) rely on data hashes for deterministic verification and state management.

• Verifying Uploads: Storing the hash of a document on-chain allows users to later prove they submitted the exact same file.
• Oracle Data Feeds: Oracles often provide data alongside its hash, allowing contracts to verify the data hasn't been altered in transit.
• Commit-Reveal Schemes: Used in voting or auctions, where a user first commits the hash of their choice, then later reveals the original data, proving they did not change it.

Digital signatures are fundamentally applied to data hashes, not the full dataset. This process is more efficient and secure.

• Signing Process: A user's private key signs the hash of a message. The signature, message, and public key can be used to verify authenticity.
• Transaction Signing: In blockchain, you sign the hash of a transaction payload, authorizing the transfer of assets or execution of a contract.
• Software Integrity: Distributors provide hashes (e.g., SHA-256 checksums) of software releases. Users can hash their download and compare it to the published hash to verify the file is authentic and unmodified.

A secure hash function must make it computationally infeasible to find two different inputs that produce the same output hash. Collision attacks undermine the uniqueness guarantee of a hash, allowing malicious data to be substituted. Modern blockchains rely on functions like SHA-256 and Keccak-256, which are currently considered collision-resistant. A theoretical break in this property would compromise the immutability of the entire ledger.

These properties ensure a hash cannot be reversed or forged.

• Preimage Resistance: Given an output hash H, it is infeasible to find any input m such that hash(m) = H. This protects the original data.
• Second-Preimage Resistance: Given a specific input m1, it is infeasible to find a different input m2 with the same hash. This prevents substitution attacks where an attacker creates a malicious document with the same hash as a legitimate one.

A hash function must be deterministic: the same input always produces the identical hash. This allows any party to independently verify data integrity by recomputing the hash and comparing it to a stored or signed value. In blockchain, this property is used to verify:

• Transaction validity (Merkle roots)
• Block integrity (linking blocks via parent hashes)
• State consistency (storage tries in Ethereum) Any deviation breaks the chain of trust.

A secure hash exhibits the avalanche effect: a tiny change in the input (even one bit) produces a drastically different, unpredictable output hash. This sensitivity is crucial for security because it:

• Makes predicting hash outputs impossible.
• Ensures that similar documents have completely unrelated hashes, preventing pattern analysis.
• Is a key feature in cryptographic functions like SHA-3, making them resistant to differential cryptanalysis.

Cryptographic hash functions can become vulnerable over time due to advances in computing (e.g., quantum computing) or newly discovered mathematical weaknesses. Algorithmic agility—the ability to migrate to a new hash function—is a critical long-term security consideration. Historical examples include the deprecation of MD5 and SHA-1. Blockchain protocols must have governance mechanisms to execute such upgrades, which are complex and require network-wide coordination.

A hash function is a deterministic, one-way cryptographic algorithm that maps data of arbitrary size to a fixed-size output (the hash). Core properties include:

• Deterministic: Same input always produces the same hash.
• Pre-image resistance: Infeasible to reverse-engineer the input from the hash.
• Avalanche effect: A tiny change in input drastically changes the output.
• Collision resistance: Infeasible to find two different inputs that produce the same hash. Common functions in blockchain include SHA-256 (Bitcoin) and Keccak-256 (Ethereum).

A Merkle Tree (or hash tree) is a data structure that efficiently verifies the integrity of large datasets. It works by:

• Leaf Nodes: Hashing individual data blocks (e.g., transactions).
• Non-Leaf Nodes: Hashing the concatenation of child node hashes.
• Root Hash: The final hash at the top of the tree, stored in the block header. This allows for Merkle Proofs, where one can verify a single piece of data is included in the set without needing the entire dataset, enabling light clients and efficient data verification.

A digital signature cryptographically proves the authenticity and integrity of a message or transaction. The process involves:

• Signing: The sender generates a hash of the message, then encrypts it with their private key to create the signature.
• Verification: The receiver decrypts the signature with the sender's public key to recover the hash, then compares it to a freshly computed hash of the received message. In blockchain, this ensures that transactions are authorized by the rightful owner of the assets and have not been altered after signing.

In Proof-of-Work (PoW), a nonce ("number used once") is a variable miners change to solve the cryptographic puzzle. The goal is to find a nonce such that the hash of the block header (which includes the nonce, previous block hash, and Merkle root) is below a specific target difficulty. This process, called hashing power or mining, secures the network by making block creation computationally expensive and easy to verify. The valid nonce serves as proof that the required work was done.

A cryptographic commitment scheme allows one to commit to a chosen value while keeping it hidden, with the ability to reveal it later. It has two phases:

• Commit: Generate a commitment (often a hash of the value plus a random salt or nonce) and publish it.
• Reveal: Later, publish the original value and salt, allowing anyone to verify it matches the earlier commitment. This is used in blockchain for confidential transactions, zero-knowledge proofs, and protocols that require binding to a secret value without immediate disclosure.

A cryptographic hash function is a one-way algorithm that deterministically maps data of any size to a fixed-size output, called a hash or digest. Key properties include:

• Deterministic: Same input always yields the same hash.
• Pre-image Resistance: Infeasible to reverse the hash to find the original input.
• Avalanche Effect: A tiny change in input produces a completely different hash.
• Collision Resistance: Extremely unlikely for two different inputs to produce the same hash. Common algorithms include SHA-256 (used in Bitcoin) and Keccak-256 (used in Ethereum).

A Merkle Tree (or hash tree) is a data structure where every leaf node is the hash of a data block, and every non-leaf node is the hash of its child nodes. This creates a single root hash that cryptographically summarizes all the underlying data.

• Efficient Verification: To prove a single transaction is in a block, you only need a small subset of hashes (a Merkle proof), not the entire dataset.
• Tamper Evidence: Changing any piece of data changes its leaf hash, which cascades up and changes the root hash, making tampering immediately detectable. This is fundamental for blockchain light clients and data availability proofs.

A commit-reveal scheme is a two-phase protocol that uses hashing to hide information temporarily before revealing it. This prevents front-running and manipulation in decentralized applications.

1. Commit: A user publishes the hash of their secret data (e.g., a bid, vote, or random number) to the blockchain.
2. Reveal: Later, the user publishes the original data. The network can verify it matches the earlier hash. This ensures the commitment was made in the first phase and cannot be changed, while keeping the data secret until the reveal. Used in voting, auctions, and random number generation.

In blockchain systems, hashes are the universal method for creating globally unique, immutable identifiers.

• Transaction ID (TXID): The hash of a transaction's data.
• Block Hash: The hash of a block's header, serving as its unique fingerprint and linking it to the previous block.
• Smart Contract Address: On Ethereum, a contract's address is derived from the hash of the creator's address and nonce.
• State Root: The hash representing the entire state of the blockchain (account balances, storage) at a given block. These hashes create an immutable, verifiable chain of reference.

A hash collision occurs when two different inputs produce the same hash output. For cryptographic hashes, this must be computationally infeasible.

• Security Implications: A practical collision attack would break the fundamental guarantees of data integrity, allowing forged signatures or fraudulent data to appear valid.
• Algorithm Evolution: Older algorithms like MD5 and SHA-1 are considered cryptographically broken due to discovered collision vulnerabilities. Modern blockchains use SHA-256 or Keccak-256, which remain secure against all known practical attacks. The security of the entire blockchain rests on the collision resistance of its underlying hash function.