Dynamic Difficulty Scaling for Proof-of-Work Consensus Protocol

dc.contributor.authorTupwong A.
dc.contributor.authorSuttichaya V.
dc.contributor.correspondenceTupwong A.
dc.contributor.otherMahidol University
dc.date.accessioned2025-06-14T18:17:03Z
dc.date.available2025-06-14T18:17:03Z
dc.date.issued2025-01-01
dc.description.abstractBlockchain technology is widely utilized across various sectors, including economics and intellectual property, with consensus algorithms being fundamental to ensuring security and functionality. Proof-of-Work (PoW) is a fundamental consensus mechanism in Bitcoin, requiring significant computational resources, with GPUs outperforming CPUs in mining efficiency. A critical vulnerability in PoW is the {5 1 \%} attack, where dominant mining nodes gain disproportionate control of the network. This study proposes the Dynamic Difficulty Scaling Factor for Proof-of-Work (DPoW), a novel approach designed to mitigate this issue. DPoW adjusts mining difficulty based on a node's previous unsuccessful attempts, allowing nodes with lower computational power to face reduced difficulty levels. This dynamic adjustment promotes fairness, enabling less powerful nodes to compete more effectively against stronger nodes. Experimental results demonstrate that DPoW effectively mitigates the risk of a 51% attack in PoW and ensures an equitable distribution of benefits among all mining nodes within the network.
dc.identifier.citation2025 17th International Conference on Knowledge and Smart Technology Kst 2025 (2025) , 237-242
dc.identifier.doi10.1109/KST65016.2025.11003374
dc.identifier.scopus2-s2.0-105007537375
dc.identifier.urihttps://repository.li.mahidol.ac.th/handle/123456789/110714
dc.rights.holderSCOPUS
dc.subjectBusiness, Management and Accounting
dc.subjectComputer Science
dc.subjectDecision Sciences
dc.titleDynamic Difficulty Scaling for Proof-of-Work Consensus Protocol
dc.typeConference Paper
mu.datasource.scopushttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=105007537375&origin=inward
oaire.citation.endPage242
oaire.citation.startPage237
oaire.citation.title2025 17th International Conference on Knowledge and Smart Technology Kst 2025
oairecerif.author.affiliationMahidol University

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