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Related Experiment Video

Updated: Jun 18, 2025

Knowledge Based Cloud FE Simulation of Sheet Metal Forming Processes
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Trust value evaluation of cloud service providers using fuzzy inference based analytical process.

Jomina John1, K John Singh2

  • 1School of Computer Science Engineering and Information Systems, Vellore Institute of Technology, Vellore, Tamil Nadu, 632014, India.

Scientific Reports
|August 4, 2024
PubMed
Summary

This study introduces a fuzzy logic-based trust evaluation model to enhance cloud service adoption. It addresses the lack of trust between cloud users and providers by assessing Quality of Service (QoS) factors.

Keywords:
Cloud computingCloud securityCloud service providerFuzzy logicTrust modelTrust parametersTrust score

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Area of Science:

  • Computer Science
  • Information Security
  • Cloud Computing

Background:

  • Cloud computing offers significant advantages for IT and healthcare but faces adoption barriers due to trust issues between Cloud Service Users (CSUs) and Cloud Service Providers (CSPs).
  • Existing trust models are varied, necessitating a robust methodology for selecting appropriate cloud services based on user needs.
  • A comprehensive evaluation framework is crucial for assessing cloud service trustworthiness.

Purpose of the Study:

  • To propose an accurate, fuzzy logic-based trust evaluation model for assessing Cloud Service Provider (CSP) trustworthiness.
  • To analyze the impact of fuzzy logic on improving the efficiency of trust evaluation in cloud environments.
  • To identify essential elements for a comprehensive cloud service evaluation.

Main Methods:

  • Development of a fuzzy logic-based trust evaluation model.
  • Assessment of trust using Quality of Service (QoS) parameters including security, privacy, dynamicity, data integrity, and performance.
  • Simulation of the proposed model using MATLAB.

Main Results:

  • The fuzzy logic-based model effectively evaluates the trustworthiness of cloud service providers.
  • Fuzzy logic enhances the efficiency and accuracy of trust assessment in cloud computing.
  • MATLAB simulations validated the proposed model's viability in a cloud setting.

Conclusions:

  • The proposed fuzzy logic model provides a viable solution for evaluating cloud service trustworthiness.
  • Addressing trust concerns through robust evaluation models can accelerate cloud computing adoption across industries.
  • Quality of Service (QoS) characteristics are key metrics for building trust in cloud environments.