This is due to the Merkle tree's widespread use in the domain of blockchain. In fact, following the collapse of the Centralized Exchange (CEX) FTX, many CEXs have started a trend of implementing Merkle trees as a form of Proof of Reserves (PoR) to reassure users of their fund's security.
In this blog, we will explore the concept of Merkle trees, including how they work and their role in the blockchain. We'll also go over some of the benefits of using Merkle trees, such as their ability to verify data integrity and their storage and computation efficiency. So, whether you are a cryptocurrency enthusiast or a computer science enthusiast, this blog post has something for you.
A Merkle tree, also known as a hash tree, is a data structure that is used in the field of cryptography to verify the authenticity and integrity of data. It does this by generating a unique cryptographic hash for each piece of data and then organizing these hashes in a tree-like structure. These hashes are unique values obtained after encoding files to a fixed and smaller value than the original file.
In computer science, a Merkle tree is a tree-like data structure made up of nodes, with each node representing a hash of some data. Hashes are then used to verify the authenticity and integrity of the data by ensuring that the hash of the data matches the hash of the root node.
The Merkle Tree concept is named after computer scientist Ralph Merkle, who patented it in 1979. Then in 1987, he published the paper "A Digital Signature Based on a Conventional Encryption Function," which used this concept. He is mainly known for his work on public-key cryptography and cryptographic hashing.
The Merkle tree is fundamentally a binary tree structure, which means that each node can have up to two children. Each node authenticates the sub-nodes and represents the hash of the sub-nodes. They are used in distributed systems to verify data efficiently by storing it in hashes rather than entire files. Popular blockchain networks such as Bitcoin and Ethereum use merkle trees to store and verify large amounts of transaction data more securely and efficiently.
So, before we can understand the workings of a Merkle tree, we must first understand its structure and components.
Leaf nodes: These are the tree's lowest nodes and the beginning of the tree. They represent the individual data points that will be summarized by the tree. Each leaf node contains the hash of a single piece of data.
Non-leaf nodes: These are intermediate nodes located between the leaf nodes and the root node. They contain the intermediate hash of the combined data from their child nodes.
Root node: It is the topmost node in the tree. It contains the hash of the combined data from all of the leaf nodes in the tree and this final hash is known as the "Merkle root."
Hash function: The hash function is a mathematical function that takes an input of any size and generates a unique and fixed-size output, known as a "hash value." The hash function is used to generate the hashes that are stored in the leaf and non-leaf nodes of the tree. For example, the SHA-256 algorithm is used in Bitcoin to perform calculations and generate output in form of hashes.
Hash values: These are the outputs of a hash function, which are used to represent the data stored in the leaf and non-leaf nodes. The hash values are used to verify the integrity of the data in the tree.
In the context of blockchain, a Merkle tree is a data structure that is used to store the transactions in a block in a decentralized and distributed ledger. The transactions are stored in the leaf nodes of the tree, and each non-leaf node contains the intermediate cryptographic hashes. This structure allows for efficient and secure verification of the transactions contained in the block.
When a new transaction is made, it is added to a leaf node in the tree. Then, the hash function calculates the cryptographic hash of the transaction. These hashes generated are stored in the leaf node. The leaf nodes are then paired, and the hashes of the two nodes are combined and hashed again, creating a new non-leaf node. This process is repeated until there is only one node left in the tree, called the root node.
Every leaf node represents a hash of transactional data, and every non-leaf node represents a hash of its previous hashes. It's worth noting that merkle trees are binary trees, so they must have an even number of leaf nodes. So, if the number of transactions is odd, the last hash will be duplicated and combined to create an even number of leaf nodes.
Source: Techskill Brew
Let’s have a clear look with the help of this diagram. Imagine a block with five transactions, each with its own unique hash: Hash A, Hash B, Hash C, Hash D, and Hash E. As these hashes are paired and combined, a tree-like structure is formed. The combination of Hash A and Hash B gives us Hash AB, and similarly, the combination of Hash C and Hash D results in Hash CD.
But what happens when we have an odd number of hashes, as is the case with Hash E? In order to maintain the binary nature of the Merkle tree, this lone hash is duplicated and hashed with itself to create Hash EE. From here, Hash AB and Hash CD are joined to form Hash ABCD, while Hash EE is duplicated once more and hashed with itself to become Hash EEEE. These two hashes are then combined to generate the Hash ABCDEEEE which is the ultimate representation of all the transactions in the block. However, it must be noted that this is just a simple illustration of a merkle tree. In reality, the hash functions generate much more complex hashes, making this process time-consuming and complex.
Now, the root node of the Merkle tree is obtained by combining and hashing all the nodes. By creating a hash (Merkle root) of the entire set of transactions, a Merkle tree stores all transactions in a block. After this process, Merkle root is added to the block header, along with other metadata such as the previous block's hash and a timestamp.
The block is then broadcast to the network for validation. Each node in the network independently verifies the transactions in the block by recalculating the hashes in the Merkle tree and checking that the root node of the tree matches the one in the block header. If the hashes match, then the validator can confirm that the data is included in the block.
In a nutshell, each transaction is hashed and added to the tree, and the root value of the tree is included in the block header. Then the block is broadcasted to the network. It enables the nodes to determine whether a transaction is valid by recalculating and matching the hashes with the Merkle root in the block header.
There are several benefits of using a Merkle tree in a blockchain:
Efficient verification of transaction: Merkle tree makes the validation of a block’s data much faster by compressing the entire data into a root hash. This reduces the size of the block header and allows more transactions to be included in a block.
Increased scalability: Merkle trees allow nodes to validate transactions without needing to store the entire transaction history of the blockchain. This makes blockchain scalable by allowing it to handle a larger number of users without incurring excessive computational expenses.
Improved Security: A Merkle tree’s structure ensures that any changes to the transactions in a block will be detectable by the changes they cause to the root hash. This makes it more difficult for an attacker to alter a block without being detected, improving the blockchain's overall security.
Simplified data storage: Merkle trees allow nodes to store only the root hash of the tree, rather than the entire set of transaction data. This reduces the amount of data that needs to be stored, making it more practical to maintain a decentralized, distributed ledger.
Versatility: Merkle trees can be used to validate any type of data, not just transactions. This makes them a valuable tool for a wide range of applications other than blockchain technology.
To conclude, a Merkle tree is a data structure that is used to validate a set of data. It is useful in the context of blockchain technology because it enables efficient verification of large amounts of data as well as efficient data storage.
Merkle trees are mathematical data structures composed of hashes of various data blocks that serve as a summary of all transactions in a block. Each leaf node is a hash of a data block, while each non-leaf node is a hash of its children. It also allows for the efficient and secure verification of large amounts of data. It also helps with data consistency and content verification.