skip to main content
10.1145/3532213.3532239acmotherconferencesArticle/Chapter ViewAbstractPublication PagesiccaiConference Proceedingsconference-collections
research-article

A Computational Trust Model Based on Hyperledger Fabric Blockchain

Published: 13 July 2022 Publication History

Abstract

The core component of the blockchain is smart contracts, which are the basis for connecting countless nodes and executing transactions. In smart contracts, trust often replaces trust in the form of proof of workload, proof of identity, proof of authorization, etc. Therefore, in the transaction process of the core chain, the node usually sees a concept of quantity, and does not know the change course of the agent's trust, so that it cannot fully grasp the dynamic process of the agent and the change of the trust evaluation value. The researches of computational trust has deeply affected the global economic and social development, and have been widely used in some large platforms such as ICAO PKD trust platform, EU's eIDAS platform, US FICAM system and so on. The current solution is a combination of limited mathematical models and assumptions that are far from the operational level. Hyperledger has superior performance in data access, invocation, operability, tamperability, traceability and other aspects, and is more suitable for the study of computational trust models. This study introduces the hyperledger technology to construct a computational trust model, and the main factors affecting the computational trust model are analyzed by using the Hyperledger Fabric technology, which is as the form of one to one to correspond to each node in the hyperledger, and realizes the trust transmission of the node, by sorting each node in the consensus chain, and passes. The interface technology realizes the docking between the model and the Hyperledger Fabric system. And then this paper analyzes the composition system of the computational trust model based on Hyperledger Fabric.

References

[1]
Xu Wu, A trust-based detection scheme to explore anomaly prevention in social networks, Knowledge and Information Systems, (2019) 60:1565–1586.https://doi.org/10.1007/s10115-018-1276-9
[2]
Shen C, Shi L, Zhang H, Liu C, Shang Z, Trusted Computing and Trusted Cloud Security Framework[J]. Science and Management, 2018, 38(2):1-6
[3]
Aynaz K, MohammadReza K, TP-TA: a comparative analytical framework for trust prediction models in online social networks based on trust aspects, Artif Intell Rev (2019) 52:1929–1960, https://doi.org/10.1007/s10462-017- 9583-1
[4]
Hyun-Kyo Oh, Jin-Woo Kim, Sang-Wook Kim, Kichun Lee, A unified framework of trust prediction based on message passing[J]. Cluster Computing, (2019) 22:S2049–S2061,https://doi.org/10.1007/s10586-018-1807-x.
[5]
Hu J,Shen C,Gong B,Tusted Computing 3.0Engineering Fundamental [M].Posts & Telecom Press,2017.
[6]
Youssef M, Abdeslam EN, Mohamed D, Towards a framework for the analysis and evaluation of computational trust models in multi-agent systems[J]. J Softw, 2017, 12(11):892–905
[7]
Marsh S, Formalising trust as a computational concept. University of Stirling, Stirling, 1994
[8]
Marsh S, Dibben MR, Trust, untrust, distrust, and mistrust—an exploration of the dark (er) side. In: Proceedings of the trust management conference, Paris, France, May 23–26, 2005. Springer, Berlin, pp17–33
[9]
Lewicki RJ, McAllister DJ, Bies RJ, Trust and distrust: new relationships and realities. Acad Manag Rev,1998, 23:438–458
[10]
Sztompka P, Trust: a sociological theory. Cambridge University Press, Cambridge,1999
[11]
Josang A, Ismail R, Boyd C, A survey of trust and reputation systems for online service provision.Decis Support Syst,2007,43(2):618–644
[12]
Fang H, Bao Y, Zhang J, Leveraging decomposed trust in probabilistic matrix factorization for effective recommendation. In: Proceeding AAAI’14 proceedings of the twenty-eighth AAAI conference on artificial intelligence. AAAI Press, Qubec, Canada, 2014,pp 30–36
[13]
Yan Z, Kantola R, Shi G, Zhang P, Unwanted content control via trust management in pervasive social networking. In: 2013 12th IEEE international conference on trust, security and privacy in computing and communications.
[14]
Jiang W, Wang G, Bhuiyan MZA, Wu J, Understanding graph-based trust evaluation in online social networks: methodologies and challenges. ACM Comput Surv, 2016, 49(1).
[15]
B. Christianson and W. S. Harbison. Why isn't trust transitive? In M. Lomas, editor, Proceedings of the Security Protocols International Workshop, volume 1189 of LNCS, pages 171–176. Springer, Berlin, 1996.
[16]
Christiano Castelfranchi and Rino Falcone. Trust Theory: A Socio-cognitive and Computational Model. Wiley Series in Agent Technology. Wiley, New York, 2010.
[17]
Victor P, Cornelis C, De Cock M, Trust networks for recommender systems. Springer, Berlin,2011
[18]
Zheng X, Trust prediction in online social networks, PhD Thesis, Macquarie University, 2015
[19]
Ashtiani M, Abdollahi Azgomi M, A novel trust evolution algorithm based on a quantum-like model of computational trust. CognTechnol Work, 2019,21:201–224
[20]
Ashtiani M, Abdollahi Azgomi M, A formulation of computational trust based on quantum decision theory. Inf Syst Front, 2016, 18:735–764.
[21]
Sel M . A Comparison of Trust Models[C]// Springer Vieweg, Wiesbaden, 2015.
[22]
Inglehart R, Welzel C. Modernization, Cultural Change, and Democracy: The Human Development Sequence [M]. New York:Cambridge University Press,2005.
[23]
Aquino D, Alves J . The Meaning of Trust for Brazilians with Higher Education [J]. Social Indicators Research, 2017, 130(1):325-349.
[24]
Braynov S. Contracting with Uncertain Level of Trust[C]// Acm Conference on Electronic Commerce. ACM, 1999.
[25]
Harz D, Boman M. The Scalability of Trustless Trust [J].Financial Cryptography and Data Security, 2018:279-293.
[26]
Chen H-C.A, Trust Evaluation Gateway for Distributed Blockchain IoT Network[C]. International Wireless Internet Conference.Springer, Cham, 2019.
[27]
Litos O S T, Zindros D. Trust Is Risk: A Decentralized Financial Trust Platform[M]// Financial Cryptography and Data Security. Springer, Cham, 2017.
[28]
Shala B, Wacht P, Trick U, Trust Integration for Security Optimisation in P2P-Based M2M Applications[C]// 2017 IEEE Trustcom/BigDataSE/ICESS. IEEE, 2017.
[29]
Wamba S F. Continuance Intention in Blockchain-Enabled Supply Chain Applications: Modelling the Moderating Effect of Supply Chain Stakeholders Trust[J].Information Systems, 2018:38-43.
[30]
Léo Mendiboure, Chalouf M A, Krief F. Towards a Blockchain-Based SD-IoV for Applications Authentication and Trust Management[J].Internet of Vehicles. Technologies and Services Towards Smart City, 2018:265-277.
[31]
Smith K, Dhillon G. Supply Chain Virtualization: Facilitating Agent Trust Utilizing Blockchain Technology [J].Revisiting Supply Chain Risk, 2018:299-311.
[32]
WANG Q, HONG W, HUANG C, Study on the Computational Trust and Its Model, 2019 2nd International Conference on Communication, Network and Artificial Intelligence, CNAI 2019.
[33]
Qingnian WANG, The Structure of a Computational Trust Model Based on Hyperledger Fabric, Basic & Clinical Pharmacology & Toxicology, 2020.08
[34]
Qing-Nian WANG, Dan-Xia QIU, Research on the Innovation of E-commerce Talent Cultivation Model in Application-oriented Colleges, 2019 5th International Conference on Modern Education and Social Science (MESS 2019), ISBN: 978-1-60595-660-2.

Recommendations

Comments

Information & Contributors

Information

Published In

cover image ACM Other conferences
ICCAI '22: Proceedings of the 8th International Conference on Computing and Artificial Intelligence
March 2022
809 pages
ISBN:9781450396110
DOI:10.1145/3532213
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 13 July 2022

Permissions

Request permissions for this article.

Check for updates

Author Tags

  1. Application
  2. Computational Trust
  3. Hyperledger Fabric

Qualifiers

  • Research-article
  • Research
  • Refereed limited

Funding Sources

  • National Social Science Fund of China
  • the state Project of Ministry of Science & Technology of China
  • Guangdong Natural Sciences Fund
  • the Humanities and Social Sciences Fund of South China University of Technology

Conference

ICCAI '22

Contributors

Other Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

  • 0
    Total Citations
  • 92
    Total Downloads
  • Downloads (Last 12 months)16
  • Downloads (Last 6 weeks)0
Reflects downloads up to 16 Feb 2025

Other Metrics

Citations

View Options

Login options

View options

PDF

View or Download as a PDF file.

PDF

eReader

View online with eReader.

eReader

HTML Format

View this article in HTML Format.

HTML Format

Figures

Tables

Media

Share

Share

Share this Publication link

Share on social media