Research on Big Data Storage Method based on IPFS and Blockchain

Abstract

With the popularity of digital cryptocurrency such as bitcoin, blockchain, as a new distributed framework with decentralization, non rewriting and traceability, has sprung up rapidly and has been applied in many industries such as finance, medical treatment, information security, etc. In order to ensure the security of transaction data, all key information in the business needs to enter the blockchain network. In the field of artificial intelligence, model data (i.e. effective feature point data set) will be the key information and will be used frequently. However, these feature point datasets may be megabytes, auspicious, or even terahertz. Then, the performance of big data transaction in blockchain network will be a problem worthy of study. Therefore, this paper proposes a blockchain big data storage method based on IPFs. This method mainly solves the transaction performance problem of large text data in the blockchain network. The data larger than 100 megabytes are stored in IPFs to obtain the hash certificate of text. The hash code is the only transaction voucher in the blockchain network. It greatly improves the transaction efficiency of blockchain network. In this paper, a comparative experiment is set up to further prove the efficiency of our method.