# Towards Trust and Friendliness Approaches in the Social Internet of Things
## 4 Classification of Trust- and Friendliness-Based Approaches in the Social IoT
### Trust Formation
#### 4.6.2 Multi-Trust  
Multi-trust always implements trust in a multidimensional way. It means there are multiple trust properties considered for the formation of trust. For example, [PERSON] and [PERSON] [30] considered various trust properties together, including honesty, intimacy, and unselfishness. These properties are used for MANETs. Moreover, there are multiple ways to enact trust formation. Some of them are described below. * First is where one person can easily use trust properties without combining them. He/she has a minimum threshold value for each trust property, which is based on application-based requirements [23]. * One can use a trust scale by using a confidence technique for trust establishment. This idea is used to scale the most important properties with less important properties, which represents confidence. As previously stated, that confidence value is used to establish trust among multiple persons. * One can use the weighted sum. This is the aggregate of individual trust values. Moreover, assigned weight can reflect the application-based requirements [57]. Open Discussion, Challenges In, and Future Research Directions for Trust- and Friendliness-Based Approaches in the Social IoT  
In the previous section, we reviewed current methods for trust- and friendliness-based approaches in the social IoT. These are based on our classifications. We summarized main areas that have not been well investigated by using current studies. In this section, we will discuss main open issues, challenges, and their possible remedies, with a focus on several aspects. Based on the discussion of the above survey, we can find a number of issues in the area of trustworthiness and friendliness in the SIoT. First, trust evaluation lacks concern with context awareness and the user's (trustor's) subjective properties. Evaluation of trust-computed results is not personalized. Thus, it is hard to provide IoT services. So, our finding is that \"only me, only now, and only here\" kinds of services are still an unachieved target. The second finding is that there is still a lack of literature and trusty frameworks that can provide all proposed trust objectives. Previous concerns, such as the subjective and objective models proposed in some research [24] are still in the evaluation phase, and hence, cannot be completely used for practice in trusty social networks. The third aspect is the trusted computing platforms used for the social IoT and cloud platforms [15] that have been proposed. They could be too complicated or heavy for tiny sensors to adopt. There is a need to introduce a lightweight solution for sensors (because they have limited computation and memory capabilities). The fourth aspect is regarding industry 4.0 and the SIoT. We identified several studies related to the IoT and industry 4.0. But little attempt was made with respect to social networks. There is a need to explore the relation between the SIoT and industry 4.0 in detail. We already know that a lot of data are generated by social networks. Hence, the integration of social media and the IoT has been witnessed in various areas, such as traffic routing, product design, etc. [25]. It could be helpful, in the future, to use trusty social networks in the automation of industries. Fifth is the relationship between objects using OOR or POR [14; 33], which are helpful in finding human object location. Researchers are working on the findings of real-time GPS tracking systems. The concept of OOR would be helpful in this regard. We carefully investigated the literature but found a limited attempt at it. Additionally, if trust is incorporated into POR, it will be better. Sixth is the service search. Link selection and service search are the backbone of social networks. Numerous researchers presented their work [49], and people are still working on this idea to make more greedy methods for the selection of links. There are many heuristic-based algorithms that have already been proposed [14]. But these methods are not effective.