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When blockchain meets IoT: a comparison of the performance of communication protocols in a decentralized identity solution for IoT using blockchain.

Authors :
Sharma, Prakhar
Wilfred Godfrey, W.
Trivedi, Aditya
Source :
Cluster Computing. Feb2024, Vol. 27 Issue 1, p269-284. 16p.
Publication Year :
2024

Abstract

Internet of Things (IoT) is a rapidly expanding technology composed of devices embedded with sensors, specialized hardware, and software to connect with other devices and servers on the internet. With this rapid expansion, it faces some major hurdles in data secrecy, privacy, and device integrity, and perhaps, in general, digital identity has been a major problem on the internet. The World Wide Web Consortium (W3C) has provided a standardized format through which one can specify his identity called Decentralised Identifiers (DIDs). Blockchain technology, alongside decentralized identifiers and public-key cryptography, offers a peer-to-peer identity and credential management model through self-sovereign identity. Combining the decentralized identity and blockchains provides us with verifiable credentials through which one can verify the identities of transacting peers by decentralized registration and discovery of public keys needed to verify digital signatures. This combined framework is trusted, permissioned, supports device registration and verification along with revocation of device credentials, is secure, respects the privacy of the participating nodes, and maintains the integrity of their data. With several new communication protocols being developed for IoT and leveraging the Blockchain protocols in the domain of IoT, this paper quantitatively compares the performance of the well-known IoT communication protocols such as CoAP, MQTT, and DIDComm in real-time testbed on various parameters, and the results are tabulated. Device data has also been replicated across multiple peers using decentralized storage such as InterPlanetary File System (IPFS). [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
13867857
Volume :
27
Issue :
1
Database :
Academic Search Index
Journal :
Cluster Computing
Publication Type :
Academic Journal
Accession number :
175635319
Full Text :
https://doi.org/10.1007/s10586-022-03921-8