# Trust-Aware Fog-Based IoT Environments: Artificial Reasoning Approach
## 2 Related Work
### Fog-Based Distributed Trust Models  
Several studies use the distributed approach such as [10; 30; 36]. [PERSON] et al. [30] design a Fog COMputIng Trust manageMENT (COMITMENT) system. They consider direct and indirect trust in calculating the overall trust level of the participating nodes. In the direct trust, QoS (e.g., low latency) and quality of protection (QoP) (e.g., data protection) metrics are used to assess the trust level of selected Fog nodes by adopting the Bayesian network method. In the indirect trust, recommendations from neighboring Fog nodes are used to assess the trustworthiness of participated Fog nodes by adopting the distributed Collaborating Filtering method. In this system, two types of recommenders, namely trusted Fog nodes and community Fog nodes, are considered to evaluate the relationships between the trustor Fog node and the recommenders. If the recommender is a trusted Fog nodewith a satisfactory experience score, the recommendation will be considered; otherwise, the recommendation will be ignored. Whereas if the recommender is a community Fog node, it will be considered if it has similar standards (e.g., same QoS and QoP experience) with the trustor. [PERSON] et al. [10] develop a two-way TMS based on subjective logic. In this study, three QoS parameters were utilized by the service provider (Fog server) to evaluate the truthfulness of the service requester (Fog client), namely friendship, honesty, and ownership. At the same time, the Fog client evaluates the trust level of the Fog server in delivering stable and secure services by utilizing three social relationship metrics: latency, ownership, and packet delivery ratio. [PERSON] et al. [36] propose a hierarchical trust management architecture based on blockchain with mobility support in the Internet of Everything (IoE)-based systems. The trust values of IoT devices are stored in the blockchain maintained by distributed Fog nodes. The trust model considers the honesty of IoT devices to report recommendations to their managing Fog nodes about other service providers. So, they only focused on recommendations and ratings. [PERSON] et al. [37] propose a TMS for mobile Fog computing services. In this model, three parameters are used to evaluate the direct trust of sensor nodes: residual energy, node communication interaction, and packet loss rate. The overall trust score considers recommendations with direct trust. [PERSON] and [PERSON] [11] propose a bi-directional trust management system to fulfill both secure offloading and fog-to-fog collaboration. The model allows a service requester to calculate the trustworthiness of the service providers and vice versa before any transaction. The proposed model uses QoS, level of security, and social relationships to compute the trust level of a node by fusing these trust parameters with past reputation and recommendations from other neighboring nodes. [PERSON] et al. [38] propose a lightweight multidimensional trust evaluation mechanism in the service-oriented IoT edge environment. The overall trust in the proposed model is developed to assess the IoT edge devices, which are divided into three parts: direct trust, capability trust, and indirect trust from feedback. Furthermore, a double-filtering mechanism based on multi-source feedback is developed to ensure the correctness and reliability of indirect trust. Finally, the trust evaluation process is completed by IoT edge devices and the edge server without the involvement of the cloud server. [PERSON] et al. [39] offer a Fog-based middleware in which trust agents compute the approximated interpersonal trust between a Fog node and the Cloud. The entropy definition is used to perform the trust computation in a decentralized manner. In order to improve and maintain trust, the Fog architecture uses a service layer on top of the Fog. [PERSON] and [PERSON] [40] present a Trust and Reputation-based Model called TRFIoT for Fog-based IoT to evaluate the trustworthiness of Fog nodes.