# Toward a Trust Evaluation Mechanism in the Social Internet of Things
## 3 Trust Evaluation Model: Background and Provisions
### Related Work on Trust Evaluation
An interesting article is about judging trust based on several features extracted from social interactions such as spatiality, relative orientation, frequency of interactions, and duration of interactions [30]. However, this information is not sufficient to accurately derive trust due to a variety of assumptions on relations between trust and behaviors of entities which are sometimes not correct. Some trust models imitate the human cognitive process to form a belief value by considering several types of TIs such as reputation and recommendation and observation. These models have been proposed for trust evaluation and trust management in P2P networks [31], Social Networks [32], IoT [23; 33] and in SIoT [34]. Most of them are based on interactions among entities in (social) networks to evaluate trust, resulting in a distributed, activity-based or encounter-based computation model. Here, trust is derived only based on social concepts such as reputation, recommendation and experience by propagating knowledge among entities. Reputation has been widely used in many applications and e-Commerce websites such as eBay, Amazon, and IMDb, however, the biggest drawback of these reputation schemes are the requirements of human participants in giving feedback as their opinions about the entities they have interacted with. In addition to the online transactions in e-Commerce, reputation schemes can be used in purely P2P, MANETs and WSNs systems that facilitate interactions among entities distributed over a network. For instance, many trust-based routing protocols in WSNs and MANETs assess trustworthiness of a node in the networks by considering third-party opinions and reputation as well as their own experiences based on their understanding to make sure that a node is not going to be misbehavioured and compromised. Based on the trustworthiness value, a decision maker will choose whether the node is put into routing paths or not. For example, a time-sensitive and context-dependent trust scheme in MANET is proposed as a combination of self-measurement and neighbor sensing (as recommendation) for enhancing trust evaluation accuracy [35]. [PERSON] et al. in [34] have also proposed a trust management scheme in the SIoT that incorporates several TIs extracted from feedbacks such as credibility, relationship factors, and transaction factors; as well as incorporates some TIs from direct knowledge such as computational capabilities showing the potentiality of an object to damage other objects. Another notion of trust is ranks among webpages introduced by Google in their PageRankTM mechanism [8]. In this example, webpages are listed in descending orders of levels of trust of the trust between a user and a webpage. The trust goal in this case is that the webpages should be the correct targets the user is searching for. The mechanism actually assesses a composite of reputation and importance of a webpage by observing network behaviors with an assumption that \"the more back-links to a webpage, the more reputation and importance it gets (and higher probability users will visit such webpage)\". In this sense, PageRankTM value is partial trustworthiness of a webpage and it is used as a TI. Even though PageRankTM is just a portion of trust and does not carry some important characteristics (e.g., subjectiveness and transitivity); in this webpage ranking scenario, it is effectively used on behalf of trust.