An Integrated Blockchain Approach for Provenance of Rotorcraft Maintenance Data

• Published in: 2020 IEEE Aerospace Conference pp. 1 - 8
• Main Authors: Zayas, Javier Ramirez, O'Neill, Eduardo, Seale, Maria A., Ruvinsky, Alicia, Eslinger, Owen
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.03.2020
• Subjects: Big Data applications; Blockchains; Data models; Ecosystems; Maintenance; Research and development; Secure storage; Security; Stability analysis; Streams
• DOI: 10.1109/AERO47225.2020.9172700

The U.S. Army Engineer Research and Development Center's Information Technology Laboratory (ITL) is creating a Data Lake Ecosystem to support efficient storage, querying and analysis of terabyte-scale datasets within a High Performance Computing (HPC) environment. The datasets contain important current and historical data, and many datasets may be related to a single subject. The ecosystem must support the ability to perform holistic analysis across datasets and must ensure data integrity and security. For the latter, it is essential to keep a record of the creation and operations performed on a Data Lake object. This type of record-keeping is called data provenance. Assured data provenance can help detect the creation, manipulation, and deletion of objects within the Data Lake Ecosystem. However, developing assured data provenance remains a critical issue. There are challenges in secure collection and storage, verifiability, and privacy of the provenance data. Hence, there is a need for guaranteeing the security and integrity of data provenance for a Data Lake Ecosystem. In this paper, we propose a trusted data provenance application for rotorcraft maintenance data based on blockchain technology. Blockchain-based data provenance facilitates recording and tracking by treating the data as relevant assets in a transactional network. We designed and implemented a proof-of-concept application to collect and verify Data Lake provenance by embedding the data provenance on a private blockchain platform. This application allows the replication of data provenance on every node of a trusted closed network, ensuring high availability and fault tolerance. With the proposed blockchain model, data provenance for unique Data Lake objects can be stored securely and efficiently verified. Results from evaluations demonstrate that with blockchain technology, it is possible to provide secure, immutable, and reliable data provenance that is essential for maintaining the integrity of information in a Data Lake environment.