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Download fileFAST DATA: a fair, secure and trusted decentralized IIoT data marketplace enabled by blockchain
journal contribution
posted on 2021-12-09, 09:16 authored by Akanksha Dixit, Arjun Singh, Yogachandran RahulamathavanYogachandran Rahulamathavan, Muttukrishnan RajarajanAs the world calls it, data is the new oil. With vast installments of Industrial Internet-of-Things (IIoT) infrastructure, data is produced at a rate like never before. Similarly, artificial intelligence (AI) and machine learning (ML) solutions are getting integrated to numerous services, making them "smarter". However, the data remains fragmented in individual organizational silos inhibiting data value extraction to it’s full potential. Digital marketplaces are emerging to allow data owners to monetize this data. Yet concerns like privacy, security and unfair payment settlement deter adoption of such platforms. In addition, the state-of-the-art platforms are under the control of large multinational corporations with no transparency between buyer and seller in terms of payment details, listing, data discovery and storage. In this work, a novel decentralized platform of digital data marketplace for IoT data has been proposed. The platform leverages a decentralized data streaming network to host IoT data in a reliable and fault tolerant manner. The platform ensures fair trading, data storage and delivery in a privacy preserving manner and trust metric calculation for actors in the network. In order to study the feasibility of the proposed platform, an open source library is developed using Hyperledger Fabric and data network layer built on VerneMQ, the library is deployed on a real-time Google cloud platform. The library is tested and results are analysed for throughput, overheads and scalability.
History
School
- Loughborough University London
Published in
IEEE Internet of Things JournalVolume
10Issue
4Pages
2934 - 2944Publisher
IEEEVersion
- AM (Accepted Manuscript)
Rights holder
© IEEEPublisher statement
© 2021 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.Acceptance date
2021-10-05Publication date
2021-10-15Copyright date
2021eISSN
2327-4662Publisher version
Language
- en