Merkle Trees
Explore the concept of Merkle trees, a hash-based data structure crucial for verifying data integrity and synchronization in distributed databases and blockchain systems. Understand how Merkle trees reduce data transfer in networked environments, support cryptographic commitments, and optimize data verification between nodes.
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A Merkle tree is a tree data structure widely used in cryptography and blockchain technologies. Ralph Merkle proposed Merkle trees in 1987 in his paper, "A Digital Signature Based on a Conventional Encryption Function."
Merkle trees are used in distributed systems to verify data integrity and synchronization between data blocks from multiple nodes.
Data structure
A Merkle tree is a tree structure in which every leaf node has a hash value. The tree computes hash values out of data that has cryptographic significance. The hash function used to calculate the hash value should be deterministic. A hash function should always produce the same output for a given input, regardless of the number of times it is executed. Furthermore, the output should be distinct for distinct data values.
Every internal node (branch) has a hash value computed out of the hash values from its child nodes. This process continues recursively up to the root, producing a single hash value for the root. The root's hash value is called the data structure's fingerprint.
Merkle trees are also called hash trees. A Merkle tree with only two child nodes is called a binary hash tree. Merkle trees help to resolve Byzantine errors.
