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Bommisetti, Ravi Kumar; Raj, Bhavana K.; Subbalakshmi, A. V. V. S.; Shehryar, Muhammad; Hoang, Sinh Duc

Blockchain in Trust with Reputation Management for Financial Stock Market Using Distributed Ledger Technology and Bayesian Theory Based on Fault Tolerance Model

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  • Medientyp: E-Artikel
  • Titel: Blockchain in Trust with Reputation Management for Financial Stock Market Using Distributed Ledger Technology and Bayesian Theory Based on Fault Tolerance Model
  • Beteiligte: Bommisetti, Ravi Kumar; Raj, Bhavana K.; Subbalakshmi, A. V. V. S.; Shehryar, Muhammad; Hoang, Sinh Duc
  • Erschienen: SAGE Publications, 2022
  • Erschienen in: Global Business Review
  • Sprache: Englisch
  • DOI: 10.1177/09721509221110371
  • ISSN: 0972-1509; 0973-0664
  • Schlagwörter: Business and International Management
  • Entstehung:
  • Anmerkungen:
  • Beschreibung: <jats:p> Blockchain, which is at the heart of bitcoin and other digital currencies, is a game-changing technology, particularly in the stock market and financial technology. These characteristics make blockchain adoption appealing for enhancing information security, privacy and reliability in a variety of scenarios. This article develops the trust with reputation-based management for the financial stock market. Here distributed ledger technology (DLT) has been integrated for implementing the ledger in which data is stored across a network of decentralized nodes. By this, proof-based ledger has been maintained with transparency, traceability and security. DLT here used is based on trust design in mitigating the malicious activities of the financial stock marketing technology. Then using Bayesian theory based on the fault tolerance (BDLT_FT) model has been used in improving the efficiency of DLT and financial technology. This acts as the protocol which reduces energy consumption and enhance network scalability and security in digital transactions like cryptocurrency The financial data related to blockchain cryptocurrency were collected between the time period 2000 and 2020. The dataset of the stock market is evaluated under the fault tolerance model with statistical analysis. The statistical evaluation of financial data with developed BDLT_FT expressed that there is no association between the fault tolerance and the classification error. </jats:p>