Hybrid Blockchain Architecture for Verifiable Data Provenance in Cloud Pipelines
Keywords:
Hybrid Blockchain, Data Provenance, Cloud Pipelines, Blockchain Security, Machine Learning ModelsAbstract
The current paper explores the use of Hybrid blockchain architecture to guarantee verifiable data provenance in cloud pipelines. As the cloud data systems are becoming more multifaceted and large-scale, traditional centralized practices face serious challenges in ensuring the integrity and security of the data. One of the strategies that can be used to address these challenges is the hybrid blockchain solutions which combine the benefits of both the public and the private blockchain. It is through restricting sensitive information to a confidential blockchain and at the same time allowing verification by the general public through a decentralized registry that hybrid blockchains provide a clear and unaltered history of data transactions. The current research will be able to estimate the effectiveness of incorporating hybrid blockchains into a cloud setting by implementing machine learning models geared towards estimating the success of the transaction and the performance of blockchain systems. Results have shown that hybrid blockchain design could improve security, transparency, and traceability of data flowing in a cloud data pipeline significantly, thus paving way to future research opportunities that explore scalability, real section of data, and system integration towards wider industry use.
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