## 2 Related Work
### Assessing Trust from the Trustee's Perspective  
Similarly to the CA approach, several studies [16; 17] place the responsibility on service providers to determine whether they can complete a requested task and assess the potential benefits before deciding whether to accept or decline service requests. [PERSON] in [16] introduces ConTrust, a context-aware trust model for the Social Internet of Things (SIoT), designed to help service consumers select reliable providers for task assignments. In this approach, the requester broadcasts the task, specifying its requirements, and providers evaluate their ability to fulfill the request along with the potential benefits. If a provider is willing to take on the task, it responds to the requester, who then assesses the trustworthiness of the candidates and selects a specific provider. Trustworthiness in ConTrust is measured using a weighted sum of three factors: the service provider's capability, commitment, and job satisfaction feedback. The CA model shares similarities with ConTrust in that it is also context-aware, as trust evaluation considers the task type and requirements within the specific environment where the service is provided. Additionally, the consumer broadcasts a request, and each provider evaluates its own capability to complete the task. However, the CA model differs in a fundamental way: service consumers do not select providers. Instead, trust assessment is handled by the provider itself, based on consumer feedback. A key issue with trust and reputation systems that rely solely on distributed infrastructures is that each entity only retains information about a small fraction of the entire network. As a result, knowledge about the number of available service providers is limited to local information, reducing the likelihood of selecting highly trustworthy providers [2]. This limitation does not apply to the CA approach. In CA, the request message is broadcasted to all service providers within the consumer agent's vicinity. However, unreliable providers, who are aware of their own limitations, will opt out of executing tasks they are not capable of handling. Consequently, this self-selection process increases the probability of obtaining service from highly trustworthy service providers. When a service requester no longer has control over selecting service providers, and instead, the service providers themselves decide whether to offer a service, a mechanism is needed to incentivize honest service provision. Additionally, most trust and reputation models assume that service requesters act honestly, which is often unrealistic in agent-based systems. To address these issues, [PERSON] et al. proposed in [17] a blockchain-based, two-way reputation system for the SIoT, incorporating a penalty mechanism for both dishonest service providers and service requesters. This approach evaluates a service provider's local trust, global trust, and reputation by considering both social trust and Quality of Service (QoS) factors, such as availability, accuracy, Cruciality, Responsiveness, and cooperation. After receiving a service, service requesters must provide feedback by rating the service providers. However, relying on a single cumulative rating has drawbacks: (i) it does not clarify the evaluation criteria used for assessing service providers; (ii) dishonest service requesters can intentionally lower a service provider's rating, even if the service is good; and (iii) inexperienced service requesters may struggle to provide meaningful feedback. To overcome these challenges, the authors propose a \"two-stage parameterized feedback\" system. Tlocal (local trust) is calculated in two phases: pre-service avail and post-service avail. Comparing Tlocal and Tglobal (global trust) helps detect suspicious or dishonest service requesters, who are then classified into three categories: suspicious, temporarily banned (can only request certain services), and permanently banned (prohibited from requesting any service).