# Towards Strengthening the Resilience of IoV Networks--A Trust Management Perspective
## 3 Trust Management in the Internet of Vehicles
### Trust Models
#### 3.2.2 Trust Parameters  
Trust parameters are mainly used to calculate trust values. Many parameters are introduced in the process of trust calculation, and the representative parameters are shown in Table 1. The trust parameters with high utilization rates are similarity, familiarity, confidence, co-location relationship, packet delivery ratio (PDR), Community of Interest (CoI), and so on. Moreover, the same trust parameters can be calculated in different ways. For example, the calculation of Community of Interest (CoI) [37; 48] is as follows:  
\[T_{C_{t_{I}}^{(Q_{i}Q_{j})}}=\frac{|C_{o_{i}}||C_{o_{j}}|}{|C_{o_{i}}|\cup|C_{ o_{j}}|} \tag{7}\]  
where \(C_{o_{i}}\) and \(C_{o_{j}}\) depict the interest group of objects \(i\) and \(j\), respectively. \[K_{i_{j}}^{CoI}(t)=\frac{|M_{i_{j}}^{CoI}}{M_{i}^{CoI}} \tag{8}\]  
The authors defined \(|M_{i_{j}}^{CoI}\) as the set of communities jointly owned by trustors and trustees, and \(M_{i}^{CoI}\) as the set of communities with each including the trustee as a member. Moreover, confidence has different explanations in different papers, such as in [28; 29]:  
\[C_{(i,k)}^{(t)}= \begin{cases}1&\text{if }T_{d(i,k)}^{(t)}\geq ThC;\\ 0.8&\text{if }ThT\leq T_{d(i,k)}^{(t)}\leq ThC;\\ 0&\text{if }T^{(t)}d_{d(i,k)}\leq ThT.\end{cases}  \tag{9}\]  
where \(Th_{C}\) is the confidence threshold, and \(Th_{T}\) is the trust threshold. \[\gamma=\frac{\int_{TR_{Dji}-\epsilon}^{TR_{Dij}+\epsilon}p_{s}^{N-1}(1-p)p_{f} ^{N-1}dp}{\int_{0}^{1}p_{s}^{N-1}(1-p)p_{f}^{N-1}dp} \tag{10}\]  
where \((TR_{Dji}-\epsilon,TR_{Dji}+\epsilon)\) is the confidence interval. The authors used Bayesian inference to calculate the confidence value. * _Co-Location Relationship (CLR)_--The concept of CLR is that when the trustee and the trustor are very close to each other, the trustor can easily obtain the information needed from the selected trustee, because from the perspective of position, the trustee is more reliable than other objects that are far away. The decision boundary is set according to the distance from the trustor in order to avoid the vehicle leaving the predetermined physical location, as demonstrated in [37], which gathered many parameters such as CWR, RS, CoI, MC, etc., and used the machine learning algorithm to find an optimal boundary to distinguish between trusted and untrusted nodes. * _Co-work Relationship (CWR)_--CWR describes the interaction between nodes that are service-dependent rather than physically adjacent. It is the association that one node possesses with another when providing a service, and it can be calculated \begin{table}
\begin{tabular}{p{14.2 pt} p{142.3 pt} p{142.3 pt}} \hline \hline
**No.** & **Trust Parameters** & **Contributions** \\ \hline
[46] & Source’s location, event location, rvent time & The author proposed a trust management scheme based on a crediting technique in MATLAB. \\
[47] & Information quality, role-oriented trust, effective distance & Hybrid trust management (NCT and DCT). \\ \hline \hline \end{tabular}
\end{table} 
Table 3: _Cont._by multicast interaction. This association represents the relative amount of shared multicast messages in relation to the total messages sent [37]. * _Rewards_--This parameter is used to evaluate the historical rewards between the trustee and the trustor. The more reasonable the interactions, the higher the reward value. This parameter can track the misbehavior of the trustee and view their history, so that the trustor can determine whether to have further communication with the trustee [37]. In [41; 49], using joint deep learning to evaluate the degree of trust between users and task assignors, the author designed a layered incentive mechanism to realize reasonable and fair rewards and punishments, which improved the accuracy of trust evaluation. * _Community of Interest (Col)_--Col represents the social status of the trustee and describes whether there is a close relationship between the trustor and the trustee in the social network.