Development of Privacy-Preservation of Big Data with support of Hyperledger Fabric and IPFS

Abstract

Alpesh Vaghela et al., International Journal of Advanced Trends in Computer Science and Engineering, 10(5), September - October 2021, 2930 – 2935 2930 ABSTRACT Academics and industry researchers alike find privacy-preservation of large data to be a very intriguing field of study. Data collection, storage, and processing are the three steps of big data's life cycle. At different stages of the big data life cycle, different privacy and security solutions are used. Many health-care stakeholders are working together to develop a new pattern for safeguarding people from an unknown disease while also promoting economic prosperity. The methods of big data processing and big data analytics will be employed to discover new economic growth patterns. Because the current method of data anonymization leads to data breaches, researchers needed to develop a new way of large data mining or knowledge discovery in databases (KDD), in which numerous parties share their data to identify new patterns. This study introduces a novel way for data mining privacy protection based on Blockchain and the InterPlanetary File System (IPFS) (PPDM). The authors propose leveraging Blockchain and IPFS to create the ChainPPDM approach for preserving big data privacy. The data saved on the blockchain is immutable, transparent, and safe, and it allows for decentralized storage. IPFS is a distributed file system that stores data in a decentralized manner.