Even today, many people do not understand fully the details of how Blockchain works. In many blockchains, one key piece of technology that is being incorporated into the network is the Merkle Tree. This is one crucial aspect to understand when distinguishing how we plan to ensure efficiency and reliability in the verification process.
Another thing to understand is that the Merkle Tree is not some fantastic innovative discovery, but it is a tested and accurate system which is utilized quite widely not just in Blockchain, but any trustless or peer-2-peer environment. This concept dates back to 1979, way before the Internet, let alone Blockchain. It is named after computer scientist, Ralph Merkle.
A Merkle Tree, in simple words, takes massive amounts of data, compresses it down into one string of characters which can prove which data are held within, without revealing what that data actually is. This string of characters is called a hash. Hashing is a one-way function, which means if you put in the same data, you will constantly get the same hash, but you cannot take that hash and extract the original data.
The ‘tree’ concept is a popular idea in science, and it refers to a structure which includes parents and children branching off each other. In this case, it is an upside-down tree in the sense that you begin with all the leaves (transactions/blocks) and work back to the one parent hash (Merkle Root).
This process brings multiple benefits, including speed, security, and efficiency. By using this process to consolidate data, we are enabled to do a rapid verification without revealing any actual data by matching up each hash with the Merkle Tree Root. Due to the complexity of the Merkle tree created in association with the decentralized aspect of Blockchain, it makes it very hard to alter the data found within these hashes.
The speed of a network can also be improved simply by using this technology. Instead of transferring files over the network to be verified and then sent back, one computer only needs to send the hash which can be very quickly verified. If there is a discrepancy, then hashes of the subtrees are requested until the blameworthy block is found and altered as necessary. This is much quicker than searching an entire file for one error. Naturally, this is likewise a much more effective utilization of resources.