SciChain: Trustworthy Scientific Data Provenance

TL;DR

SciChain introduces a blockchain-based system for high-performance computing that ensures trustworthy scientific data provenance with minimal performance overhead.

Contribution

It presents SciChain, the first blockchain system tailored for HPC, featuring the POST protocol for immutable and scalable scientific data provenance.

Findings

SciChain guarantees data trustworthiness effectively.

It achieves significantly lower overhead compared to existing systems.

Experimental results validate its efficiency and reliability.

Abstract

The state-of-the-art for auditing and reproducing scientific applications on high-performance computing (HPC) systems is through a data provenance subsystem. While recent advances in data provenance lie in reducing the performance overhead and improving the user's query flexibility, the fidelity of data provenance is often overlooked: there is no such a way to ensure that the provenance data itself has not been fabricated or falsified. This paper advocates to leverage blockchains to deliver immutable and autonomous data provenance services such that scientific data are trustworthy. The challenges for adopting blockchains to HPC include designing a new blockchain architecture compatible with the HPC platforms and, more importantly, a set of new consensus protocols for scientific applications atop blockchains. To this end, we have designed the proof-of-scalable-traceability (POST) protocol and implemented it in a blockchain prototype, namely SciChain, the very first blockchain system for HPC. We evaluated SciChain by comparing it with multiple state-of-the-art systems; Experimental results showed that SciChain guaranteed trustworthy data while incurring orders of magnitude lower overhead.