## 2 Related Work
### Trust Models for IoT Service Crowdsourcing  
The unique design of the CA model makes it well suited for IoT service crowdsourcing, where IoT devices offer services to nearby devices, known as crowdsourced IoT services. These services can include computing resources, energy sharing, and environmental sensing. For instance, in energy-sharing services, IoT devices acting as service providers can wirelessly transfer energy to nearby devices with low battery levels, which act as service consumers. Two key characteristics of IoT platforms necessitate specialized trust management frameworks, like the CA model; these are device volatility (IoT devices have a short lifespan, frequently joining and leaving the network) and context-aware trust (trustworthiness in IoT environments is influenced by various factors, such as the owner's reputation, the operating system, and the device manufacturer). In [8], [PERSON] et al. presented a Blockchain-Based Trust Management System (BTMS) for energy trading, integrating blockchain, trust management, and MASs to enhance security and reliability. The system is structured into four layers: a Blockchain Layer, which securely stores and encrypts trust values and feedback; Aggregator Layer, where coalitions of agents are managed by consensus-elected aggregators that assess trust and update blockchain records; Prosumer Layer, consisting of energy-producing and -consuming agents that trade energy while exchanging trust data with aggregators; and a Physical Layer, which includes distributed energy resources such as solar panels, wind turbines, and energy storage. The trust evaluation process incorporates direct and indirect assessments using a weighted average method, while multi-source feedback from aggregators is stored on the blockchain. Trust credibility is determined based on trust distortion, consistency, and reliability, ensuring accurate evaluation and identifying dishonest agents. Additionally, each agent is assigned a token, known as a Balanced Trust Incentive (BTI) unit, which is used to interact with other agents. BTI increases with honest behavior and decreases when dishonesty is detected, fostering a transparent and trustworthy energy trading environment. [PERSON] et al. [9] build upon the Blockchain-Based Trust Management System (BTMS) introduced by [PERSON] et al. [8], addressing unresolved challenges related to agent-to-agent cooperation and privacy in trust management within MASs. [PERSON] et al. identify that while the original BTMS effectively integrates blockchain with trust management to enhance security and reliability in energy trading, it lacks mechanisms to (i) foster agent-to-agent cooperation, as in dynamic and decentralized environments, agents may behave selfishly or maliciously, undermining collective system performance; and (ii) ensureprivacy preservation, as agents are concerned about their privacy and security, making it inappropriate for them to reveal trust information to others. To address these issues, [PERSON] et al. leverage game theory, treating trust evaluation as a repeated game to encourage effective agent cooperation. In this framework, agents that refuse to cooperate face penalties in subsequent rounds, as others will also decline cooperation. A Tit-3-For-Tat (T3 FT) strategy is employed, immediately penalizing noncooperative agents, with the punishment duration depending on their level of cooperation. Defaulter agents may regain their trust after cooperating for three consecutive plays. Afterwards, their cheating behavior is forgiven. To ensure secure and verifiable trust evaluation, a Publicly Verifiable Secret Sharing (PVSS) mechanism is implemented. It distributes sensitive information, such as cryptographic keys, among three entities: dealers (blockchain miners) who allocate shares, participants who store shares, and a combiner (aggregator) who reconstructs the secret based on a defined threshold. PVSS enhances security by enabling the public verification of share validity, deterring dishonest actions.