Proof by Earnestness (PoE) to determine the authenticity of subjective information in blockchains - application in supply chain risk management

Bui, HT; Hussain, OK; Prior, D; Hussain, FK; Saberi, M

Proof by Earnestness (PoE) to determine the authenticity of subjective information in blockchains - application in supply chain risk management

Bui, HT Hussain, OK Prior, D Hussain, FK Saberi, M

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Publisher:: ELSEVIER
Publication Type:: Journal Article
Citation:: Knowledge-Based Systems, 2022, 250
Issue Date:: 2022-08-17

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Field	Value	Language
dc.contributor.author	Bui, HT
dc.contributor.author	Hussain, OK
dc.contributor.author	Prior, D
dc.contributor.author	Hussain, FK
dc.contributor.author	Saberi, M https://orcid.org/0000-0002-5168-2078
dc.date.accessioned	2023-03-24T00:48:16Z
dc.date.available	2023-03-24T00:48:16Z
dc.date.issued	2022-08-17
dc.identifier.citation	Knowledge-Based Systems, 2022, 250
dc.identifier.issn	0950-7051
dc.identifier.issn	1872-7409
dc.identifier.uri	http://hdl.handle.net/10453/168299
dc.description.abstract	Blockchain is being used in various global supply chains with its ever-increasing maturity and popularity. However, in the presence of subjective information that does not have a digital footprint, blockchain application is a grey area. This is due to the difficulty in confirming the authenticity or legitimacy of information before achieving consensus on it using existing mechanisms such as Proof of Work (PoW), Proof of Authority (PoA) or Proof of Stake (PoS). In this paper, we attempt to address this issue. Specifically, we propose the Proof by Earnestness (PoE) consensus mechanism that determines the subjective information's truthfulness before further processing and formalising in blockchains. We consider supply chain risk management (SCRM) as our application area due to the vast amount of available subjective information.
dc.language	English
dc.publisher	ELSEVIER
dc.relation	http://purl.org/au-research/grants/arc/LP160100080
dc.relation.ispartof	Knowledge-Based Systems
dc.relation.isbasedon	10.1016/j.knosys.2022.108972
dc.rights	info:eu-repo/semantics/closedAccess
dc.subject	08 Information and Computing Sciences, 15 Commerce, Management, Tourism and Services, 17 Psychology and Cognitive Sciences
dc.subject.classification	Artificial Intelligence & Image Processing
dc.title	Proof by Earnestness (PoE) to determine the authenticity of subjective information in blockchains - application in supply chain risk management
dc.type	Journal Article
utslib.citation.volume	250
utslib.for	08 Information and Computing Sciences
utslib.for	15 Commerce, Management, Tourism and Services
utslib.for	17 Psychology and Cognitive Sciences
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Strength - AAII - Australian Artificial Intelligence Institute
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Computer Science
utslib.copyright.status	closed_access	*
dc.date.updated	2023-03-24T00:48:12Z
pubs.publication-status	Published
pubs.volume	250

Abstract:

Blockchain is being used in various global supply chains with its ever-increasing maturity and popularity. However, in the presence of subjective information that does not have a digital footprint, blockchain application is a grey area. This is due to the difficulty in confirming the authenticity or legitimacy of information before achieving consensus on it using existing mechanisms such as Proof of Work (PoW), Proof of Authority (PoA) or Proof of Stake (PoS). In this paper, we attempt to address this issue. Specifically, we propose the Proof by Earnestness (PoE) consensus mechanism that determines the subjective information's truthfulness before further processing and formalising in blockchains. We consider supply chain risk management (SCRM) as our application area due to the vast amount of available subjective information.

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http://hdl.handle.net/10453/168299