BSHPC: Improve Big Data Privacy Based on Blockchain and High-Performance Computing (HPC)

The vast expansion and sharp rise in data across many facets of society have made it increasingly difficult to manage big data effectively. Using traditional methods to ensure the security and privacy of users’ data is no longer sufficient. In keeping with this worry, massive data storage is still crucial. High-Performance Computing (HPC) is examined to determine the need for handling blockchain issues and protecting large data in a decentralized manner that strives for resilience. This study proposes the Big Data Storage High-Performance Computing (BSHPC) approach, which addresses big data considerations in storage management to maintain accuracy and enables the usage of blockchain. The best storage management is the primary benefit of BSHPC, as only critical data is kept on the blockchain, and other data may be kept in an off-chain database using the interplanetary file system (IPFS). Furthermore, the network's node authentication in this strategy depends on trustworthy nodes. On HPC computers, data authenticity and provenance tracking would be guaranteed, and managing large data across blockchains would be more secure. The proposed method is simulated using the Python-MPI version, and the results confirm the effectiveness of the proposed method based on performance and transactions. Moreover, the proposed method is evaluated with another study in the literature on MEC-based sharing, and it proves its effectiveness.