# Toward a Trust Evaluation Mechanism in the Social Internet of Things
## 4 REK Trust Evaluation Model in the SIoT
### Knowledge TI Evaluation Model
#### 4.2.2 User Recruitment in Mobile Crowd-Sensing Use-Case  
Most of applications and services in IoT heavily depend on massive amount of data collected from various types of sensors. However, traditional sensor network schemes have never reached to full potential or successfully deployed in the real world due to high installation cost, insufficient spatial coverage and so on. As a prospective solution for the traditional sensor networks, recently, the new sensing paradigm MCS has attracted attentions from both academia and industry [10]. MCS is a large scale sensing mechanism leveraging smart devices integrated with built-in sensors such as mobile phones, tablets, wearable devices and smart vehicles. It expands the traditional participatory sensing by involving both participatory sensory data from devices and social information from mobile social networking services [42]. MCS offers a large number of mobile sensing devices owners to share knowledge (e.g., local information, ambient context, noise level, and traffic conditions) acquired from their devices which further aggregated in cloud for large-scale sensing and intelligent mining [43] (Figure 7), thus enables a broad range of applications such as traffic planning, public safety, environment monitoring, and mobile social recommendation. One of the challenges in MCS is the recruitment of contributors for sensing tasks [44; 45]. In a crowded urban area with high number of participants, it is critical to recruit trustworthy users to collect high quality of data as well as to guarantee security, privacy and data integrity. This challenge calls for an efficient User Recruitment scheme implemented in the MCS Tasking Server for making proper selection of contributors respecting to a specific sensing task as illustrated in Figure 7 (the sensing task requested by service providers and assigned based on a mechanism deployed at the MCS [46]). Note that in order to recruit users evolving in a sensing task, the MCS Tasking Server should manage an incentive scheme as rewards for their contributions because users sustain costs (e.g., energy consumption, data subscription, and privacy and security breach) for accomplishing  
Figure 7: Mobile Crowd-Sensing System Architecture. assigned sensing tasks. The User Recruitment scheme specifies criteria for user eligibility to contribute to a crowd-sensing campaign by judging whether a user accomplishes a sensing task as expected. In other words, the MCS Tasking Server chooses contributors as it trusts to fulfil the sensing task. Therefore, this use-case turns to a trust scenario as follows:  
_Evaluate trust between the MCS Tasking Server (as the trustor) and owners of mobile devices (as the trustes), respecting to a sensing task (as the trust goal)_. A sensing task called Traffic Congestion and Accident Report is considered as follows: Report accidents and traffic congestion at a specific crossroad X. The sensing task is event-based, spatial, urgent, and nearly real-time required. Contributors should report situation of the traffic situation at the crossroad X by sending data obtained from smartphone sensors such as accelerometer, magnetometer, and GPS coordinates as well as submitting an image or a video about the traffic incidents [47; 48]. Based on the proposed Knowledge TI model, a set of TAs is deliberately chosen as following:  
* _Spatial Distance_: This TA shows the distance between a contributor and the crossroad X. The contributors should be close enough to the crossroad X so that it is able to report traffic situation correctly to the MCS server. The distance can be calculated based on the GPS coordinates of the smartphone and the crossroad X using the \"_haversine_\" formula presented in [49]. This TA belongs to the _Ability dimension_ and should not exceed the distance boundary (as a threshold). * _Availability_: Availability is a TA indicating the activeness of a user in getting connected to social activities.