Securing Big Data Integrity for Industrial IoT in Smart Manufacturing Based on the Trusted Consortium Blockchain (TCB)

Author:

Juma Mazen1ORCID,Alattar Fuad2,Touqan Basim1ORCID

Affiliation:

1. Faculty of Engineering & IT, The British University in Dubai, Dubai P.O. Box 345015, United Arab Emirates

2. Siemens Industrial LLC, Dubai P.O. Box 33734, United Arab Emirates

Abstract

The smart manufacturing ecosystem enhances the end-to-end efficiency of the mine-to-market lifecycle to create the value chain using the big data generated rapidly by edge computing devices, third-party technologies, and various stakeholders connected via the industrial Internet of things. In this context, smart manufacturing faces two serious challenges to its industrial IoT big data integrity: real-time transaction monitoring and peer validation due to the volume and velocity dimensions of big data in industrial IoT infrastructures. Modern blockchain technologies as an embedded layer substantially address these challenges to empower the capabilities of the IIoT layer to meet the integrity requirements of the big data layer. This paper presents the trusted consortium blockchain (TCB) framework to provide an optimal solution for big data integrity through a secure and verifiable hyperledger fabric modular (HFM). The TCB leverages trustworthiness in heterogeneous IIoT networks of governing end-point peers to achieve strong integrity for big data and support high transaction throughput and low latency of HFM contents. Our proposed framework drives the fault-tolerant properties and consensus protocols to monitor malicious activities of tunable peers if compromised and validates the signed evidence of big data recorded in real-time HFM operated over different smart manufacturing environments. Experimentally, the TCB has been evaluated and reached tradeoff results of throughput and latency better than the comparative consortium blockchain frameworks.

Publisher

MDPI AG

Subject

Electrical and Electronic Engineering,Engineering (miscellaneous),Computer Science (miscellaneous)

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