\section{Introduction}
\label{sec:introduction}


For some embedded systems, the monitoring system can be as important as the design of the system itself.
In the context of \ac{scs}, assessing the integrity and performance of the system along its life-cycle is crucial.
Failing to detect an anomalous activity or an attack can result in catastrophic consequences for the humans involved or the environment.
Given the current trend of digitization and increasing connectivity in all domains --- including for \ac{scs} ---, the importance and scale of monitoring will only increase in the foreseeable future.
To answer this growing need, generations of monitoring systems proposed to collect a variety of logs, reports, or events journals.
All these sources are accessible to human agents that can evaluate them and find patterns or anomalous behavior.
Although automated systems exists for each type of collected information, human agents remain the final destination for the result of the monitoring and they often make the final decision.

Trust management systems have emerged as a promising avenue alongside traditional security mechanisms in \ac{scs}. These systems are designed to calculate trust values of \ac{scs} and ensure that users can trust and rely on these systems for their critical operations. Trust management systems aim to provide transparency and accountability, allowing users to understand the basis for the trust values assigned to critical systems.

Trust management systems address concerns arising from undertrust and overtrust.
Undertrust in a system can lead to disuse or hesitancy in using critical systems, which can hinder their effectiveness and potentially compromise safety.
Overtrust, on the other hand, can result in blind reliance and negligence, leading to complacency and overlooking potential risks.
Therefore, it is essential to understand the role of trust in human-computer interaction in critical applications.
Trust management systems play a pivotal role in addressing these challenges by providing a structured framework for calculating and quantifying trust values of safety-critical systems.
This work studies trust management for \ac{scs} but only addresses the problem of undertrust.


 \subsection{Contribution}

 This paper proposes a novel trust management framework using \ac{sl} and its application to the assessment of embedded systems from indirect observations with uncertainties.
 The framework considers multinomial opinions to leverage uncertainty as a dimension contributing to trust output.
 The proposed approach relies on the cumulative fusion operation within \ac{sl} on multinomial opinions and provides arguments for the validity of the proposed definitions. 
 
 Finally, the study provides an evaluation of the framework for power consumption data from both lab and production machines.
 These case studies illustrate the effect of input information on output trust values. 
 