\section{Conclusion}
\label{sec:conclusion}

This paper introduced a novel trust management framework for \ac{cpss}, leveraging \ac{sl} to evaluate trust in uncertain indirect observations. 
Our methodology extends beyond traditional binary trust assessments, enabling the presence of uncertainties that reflects the nuanced reality of \ac{cpss} operations. 
Through case studies focusing on power consumption data, we demonstrated the framework’s adaptability and efficacy in providing detailed trust assessments.
This research underscores the importance of trust management in ensuring the safety and reliability of \ac{cpss} in the \ac{scs}, especially in dynamic conditions represented by indirect observations.
Our work makes a valuable contribution to enhancing the security and effectiveness of \ac{cpss}, providing a basis for further exploration in this area. 
As \ac{cpss} become more integral to modern infrastructure, advanced trust management solutions are essential for their successful deployment and operation.

To extend further the capabilities and versatility of this framework, the combination of various data sources and the usage of trust calibration actions are proposed. 

% Our framework shows promise in practical applications such as healthcare CPS and autonomous vehicles by allowing nuanced trust assessments amidst uncertainties in real-time. The adaptability and versatility of our approach underscore its importance for the development of reliable, user-centric \ac{cpss}.