## 2 Related Work
### Mechanisms for Promoting Honest Behavior
The node with the highest reputation weight is designated as the Selected Community Head (SCH), while the second highest becomes the Selected Monitoring Head (SMH). These leaders play key roles in mitigating selfish behavior: the SCH is responsible for encouraging selfish nodes to participate and can impose penalties on reported offenders, while the SMH monitors node behavior and flags selfish activity to the SCH. Selfish nodes are initially isolated in a separate domain, barring communication with the rest of the network. If a selfish node repeatedly fails to improve, it may face expulsion--a strict penalty. However, unlike permanent removal, HBST allows selfish nodes to rejoin the main community by improving their honesty level beyond a predefined threshold. In cases of persistent selfish behavior, a warning message is broadcasted to neighboring communities, instructing them to cease communication with the offending node as a severe consequence. In the Internet of Medical Things (IoMT), numerous smart health monitoring devices communicate and transmit data for analysis and real-time decision-making. Secure communication among these devices is essential to ensure timely and accurate patient data processing. However, establishing reliable communication in large-scale IoMT networks is both time-intensive and energy-demanding. To address this challenge, [PERSON] et al. propose in [21] BFT-IoMT, a distributed, energy-efficient, fuzzy logic-based, blockchain-enabled, and fog-assisted trust management framework. This framework employs a cluster-based trust evaluation mechanism to detect and isolate Sybil nodes. The process begins with a topology lookup module, which identifies network topology whenever an IoMT device joins or leaves the network. Next, clusters and Cluster Heads (CHs) are formed, with CHs registered on the blockchain. Each IoMT node's trust-related parameters are collected and analyzed by a trust calculator module. The computed trust scores are then stored on the blockchain. If a node's trust score falls below a predefined threshold, it is flagged as a malicious (Sybil) node and isolated from the network. The final decision on whether a node is malicious or benign is then broadcasted across the IoMT system. The fog-assisted trust framework is designed to enhance network throughput while reducing latency, energy consumption, and communication overhead. The use of fuzzy logic--which efficiently handles ambiguous and uncertain data, common in healthcare applications--improves the computational power and effectiveness of the decentralized trust management system. However, the proposed protocol assumes that CHs are inherently trusted nodes, which is an impractical assumption in most IoT environments. [PERSON] et al. in [22] aim to develop a fully distributed and scalable trust management protocol, enabling IoT devices to assess the trustworthiness of any service provider on the Internet without relying on pre-trusted entities. They introduce a decentralized trust management protocol for the Internet of Everything (IoE), leveraging blockchain technology and the fog computing paradigm. In this system, powerful fog nodes maintain the blockchain, relieving lightweight IoT devices of the burden of trust data storage and intensive computations. This approach optimizes resource usage, bandwidth efficiency, and scalability. By utilizing blockchain, the protocol provides a global perspective on the trustworthiness of each service provider within the network. A key feature of the proposed solution is its fine-grained trust evaluation mechanism--IoT devices receive recommendations about service providers not only based on the requested service but also according to a set of specific requirements that the providers can fulfill. Additionally, blockchain technology enhances the protocol's adaptability to high-mobility scenarios.