Cited by 166Blockchain Technology Applications and SecurityBlockchain Technology in Education and LearningAccess Control and Trust

PoRX: A reputation incentive scheme for blockchain consensus of IIoT

Wang, Eric Ke, Liang, Zuodong, Chen, Chien-Ming, Kumari, Saru, Khan, Muhammad Khurram·2020·Future Generation Computer Systems

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Crossref · 10.1016/j.future.2019.08.005

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32 of 32 references verified0 citation errors · 0 not checkable

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Authors
Wang, E. K., Liang, Z., Chen, C.-M., Kumari, S., & Khan, M. K.
Affiliations
  • Harbin Institute of Technology (CN)
  • Chaudhary Charan Singh University (IN)
  • King Saud University (SA)
Corresponding author
Kumari, Saru
Venue
Future Generation Computer Systems
Publisher
Elsevier BV
Published
2020-01
Volume
102
Pages
140-151
ISSN
0167-739X (ISSN-L)
OpenAlex
W2966938200
Cited by
166
References
32
Citations by year
2026: 6 · 2025: 15 · 2024: 18 · 2023: 23 · 2022: 44 · 2021: 44 · 2020: 16
FWCI
32.36
Type
journal article
Language
en
Open access
closed
Locations
Future Generation Computer Systems (publishedVersion)
Funders
  • National Natural Science Foundation of China (61572157, 2016A030313660, 2017A030313365)
  • Chinese National Funding of Social Sciences
  • Science and Technology Planning Project of Shenzhen Municipality
  • Natural Science Foundation of Guangdong Province (KQJSCX20170327161655607, JCYJ20160608161351559, KQJSCX70726103044992, JCYJ20170811155158682)
  • King Saud University (Productivity)
Topics
  • Physical Sciences › Computer Science › Information Systems › Blockchain Technology Applications and Security
  • Physical Sciences › Computer Science › Information Systems › Blockchain Technology in Education and Learning
  • Social Sciences › Sociology and Political Science › Access Control and Trust
Keywords
Industrial Internet of Things, blockchain consensus, cooperative behavior, trust in distributed systems, reward and punishment, smart contracts

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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

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