# Trust and Mobility-Based Protocol for Secure Routing in Internet of Things
## 4 SMTrust Design and Analysis  
Mostly, the IoT devices are resource-constrained in nature. A trust-based security approach is viable because it is considered to be lightweight and effective particularly for defence against RPL-specific and WSN-inherited attacks [38]. In networks and IoT environment, trust metrics help in monitoring and control the interaction between nodes. Thus, for trust management in IoT, the selection of trust metrics is crucial for accurate evaluation and calculation of trust [55] The trust measurements may vary with the type of applications, devices, and purpose [53]. In RPL routing topology, the appropriate parameters, refer to as trust metrics, play a vital role in a trustworthy route establishment, thus supporting the packet forwarding to the reliable nodes and protecting the legitimate nodes from the anomalous behaviour of the malicious nodes. In addition, in a vulnerable network, the trustworthy interaction among nodes [63] enhances the overall performance and packets delivery in the network, while combating against the routing attacks.  
This section presents the design specifications of the proposed trust and mobility-based secure routing protocol, SMTrust. A node's reliability is determined by the direct and indirect trust values. The proposed method's distinctiveness is that suitable mobility metrics are considered for trust evaluation to adapt to a mobile IoT environment. The diagrammatic model and workflow of SMTrust is based on the concepts detailed in [29].  
\begin{table}
\begin{tabular}{p{56.9 pt} p{56.9 pt} p{56.9 pt} p{56.9 pt} p{56.9 pt} p{56.9 pt} p{56.9 pt} p{56.9 pt}} \hline \hline
**Ref.** & **Domain** & **Solution Technique** & **Evaluation Model** & **Mobility** & **Trust Metrics** & **Attacks Considered** & **Research Gaps/Improvements** \\ \hline \hline
[25] & RPL attacks & fuzzy logic-based approach. & \begin{tabular}{c} Simulation and \\ Testbed \\ experimentation-- \\ Contiki/Cooja 3.0 \\ \end{tabular} & \begin{tabular}{c} Historical \\ observation; \\ Feedback; \\ Successful \\ nonce \\ \end{tabular} & Rank; Sybil & Does not consider nodes’ mobility; packet loss rate is significant; E2E delays, energy consumption, and colluding attacks are not evaluated; Does not consider the uncertainty of recommendations. \\ \end{tabular} \\ \begin{tabular}{p{56.9 pt} p{56.9 pt} p{56.9 pt} p{56.9 pt} p{56.9 pt} p{56.9 pt}} Wireless \\ Networks/ \\ Routing Attacks \\ \end{tabular} & \begin{tabular}{c} Dummy packets \\ insertion. \\ \end{tabular} & \begin{tabular}{c} Simulation--NS- \\ 2 for MANET, \\ insertion. \\ \end{tabular} & \begin{tabular}{c} Uncertainty; \\ Conçia/Contiki \\ 2.7 for IoT \\ \end{tabular} & \begin{tabular}{c} Uncertainty; \\ Contextual \\ and Indirect \\ trust; Route Trust \\ \end{tabular} & Packet dropping & \begin{tabular}{c} Pareto \\ dropping \\ attacks \\ not considered. \\ \end{tabular} \\ \begin{tabular}{p{56.9 pt} p{56.9 pt} p{56.9 pt} p{56.9 pt} p{56.9 pt}} \end{tabular} & \
\begin{tabular}{c} In groups \\ \\ \end{tabular} &
\begin{tabular}{c} A dummy packet \\ in networks creating \\ high overhead; \\ RFL-specific attacks are not considered. \\ Focus is on the energy consumption during \\ data collection process \\ and not on security and routing attacks. \\ \end{tabular} \\ \hline \hline \end{tabular}
\end{table}
Table 2: _Cont._The main components include trust metrics computation, trust index calculation, trust rating, trust value update, attacks detection, malicious nodes isolation, and trust decay and maintenance. Figure 4 depicts the diagrammatic flow of SMTrust.