Affiliations 

  • 1 Department of Computer Science and Engineering, Christ University, Bengaluru, 560074, India
  • 2 Department of Artificial Intelligence and Data Science, Nandha Engineering College, Erode, Tamil Nadu, India
  • 3 Department of Computer Science and Engineering, Galgotias University, Greater Noida, India
  • 4 Department of Information Technology, Manipal Institute of Technology Bengaluru, Manipal Academy of Higher Education, Manipal, India. m.usha@manipal.edu
  • 5 Department of Data Science and Artificial Intelligence, Sunway University, No. 5, Jalan Universiti, Bandar Sunway, Selangor Darul Ehsan, Subang Jaya, 47500, Malaysia
Sci Rep, 2025 Mar 19;15(1):9457.
PMID: 40108264 DOI: 10.1038/s41598-025-92643-z

Abstract

Enforcing a trust management model in the broker-based negotiation context is identified as a foremost challenge. Creating such trust model is not a pure technical issue, but the technology should enhance the cloud service negotiation framework for improving the utility value and success rate between the bargaining participants (consumer, broker, and service provider) during their negotiation progression. In the existing negotiation frameworks, trusts were established using reputation, self-assessment, identity, evidence, and policy-based evaluation techniques for maximizing the negotiators (cloud participants) utility value and success rate. To further maximization, a Bayesian-based adaptive probabilistic trust management model is enforced in the future broker-based trusted cloud service negotiation framework. This adaptive model dynamically ranks the service provider agents by estimating the success rate, cooperation rate and honesty rate factors to effectively measure the trustworthiness among the participants. The measured trustworthiness value will be used by the broker agents for prioritization of trusted provider agents over the non-trusted provider agents which minimizes the bargaining conflict between the participants and enhance future bargaining progression. In addition, the proposed adaptive probabilistic trust management model formulates the sequence of bilateral negotiation process among the participants as a Bayesian learning process. Finally, the performance of the projected cloud-enabled e-commerce negotiation framework with Bayesian-based adaptive probabilistic trust management model is compared with the existing frameworks by validating under different levels of negotiation rounds.

* Title and MeSH Headings from MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine.