Trust modeling in a distributed collaborative environment: application to a collaborative healthcare system.

Area of Science:

• Computer Science
• Information Systems
• Human-Computer Interaction

Background:

• Trust is crucial in distributed collaborative environments (DCEs), especially during emergencies like the COVID-19 pandemic.
• Existing trust models often overlook the influence of collaboration on trust assessment.
• This gap hinders users' ability to determine reliable collaborators and assign appropriate trust levels.

Purpose of the Study:

• To propose a novel trust model for DCEs that integrates collaboration as a core influencing factor.
• To develop a model capable of assessing trust at both individual and team levels within collaborative activities.
• To enhance the reliability and trustworthiness of participants in DCEs.

Main Methods:

• Developed a new trust model incorporating recommendation, reputation, and collaboration as key components.
• Employed weighted moving average and ordered weighted averaging algorithms for dynamic weight assignment to trust components.
• Created a healthcare case prototype to validate the proposed trust model's effectiveness.

Main Results:

• The proposed trust model effectively evaluates trust by considering collaborative activities and their goals.
• The model demonstrates the capability to assess the trustworthiness of collaborative teams.
• Dynamic weighting of trust components ensures flexibility and adaptability.

Conclusions:

• The novel trust model significantly enhances trustworthiness in distributed collaborative environments.
• Integrating collaboration as a factor is vital for accurate trust assessment in DCEs.
• The model provides a robust framework for managing trust in collaborative settings, particularly in critical situations.