## 5 Fuzzy Logic Approaches in Trust Management
### Effective Metrics and Comparative Analysis of Methods Based on These Metrics
#### 5.2.2 Simulation Environment
The simulation parameters included Media Access Control (MAC) type, propagation, antenna type, interference range, transmission range, simulation time, traffic source, packet size, and rate. The results showed that the proposed secure trust-based multipath routing system with optimal fuzzy logic outperformed existing techniques in terms of energy efficiency and network lifetime. OMNET++ simulation software was used to evaluate the packet delivery ratio (PDR) performance and transmission delay under different network scenarios [38]. The results show that the PDR increases with network speed, which is attributed to frequent connection breakages. The simulation also assessed the transmission delay, analyzed how the model minimized delays, and ensured efficient communication in the FANETs. Omnet++ simulations were used to gather empirical data on the TBCS model's performance in realistic FANET scenarios, providing insights into its effectiveness in enhancing trust, security, and communication reliability in dynamic and challenging network environments. The study in [39] was tested using the Omnet++ simulation software. The simulation involved ten Unmanned Aerial Vehicles (UAVs) and a ground control station that shared a wireless communication medium. The performance of the model was evaluated by increasing the number of UAVs in the simulation from 10 to 200. The recording module in Omnet++ tracked the end-to-end delay, providing insights into network characteristics. The model's performance was compared to established models, such as Flying Named Data Networking (FNDN) and UNION (a trust model distinguishing intentional and UNIntentional misbehavior in inter-UAV communication), to assess its effectiveness and efficiency in FANETs. The study in [40] was tested using MATLAB 2015 Ra on a laptop with Intel Core i7-8550 processors. The results showed the scheme's efficiency and effectiveness in terms of security and performance, outperforming the existing schemes in the authentication phase. The scheme achieved anonymity and traceability while minimizing the computational and time costs for each participant. In [41], MATLAB2016a simulation software was used to evaluate the performance of a method for detecting malicious nodes in wireless sensor networks. The simulation environment was a 200 m \(\times\) 200 m square area with 100 nodes divided into four clusters. The performance of the model was assessed using the recognition rate and false-positive rate metrics. The results show that the FTM-ABC strategy maintained a high recognition rate and low false-positive rate, even with a 50% number of dishonest nodes, indicating its robustness and reliability in detecting malicious nodes. In [42], MATLAB was used to simulate a 50 min hierarchical trust management scheme in wireless sensor networks. The simulations evaluated its impact on network behavior, trust levels, and overall performance, validating its effectiveness in enhancing the security and reliability of wireless sensor networks. In [46], which used a double-layer blockchain architecture for trust evaluation in SDNs, a detection rate of up to 98.89% was achieved in simulations using Mininet and the POX controller. This high detection rate demonstrates the ability of the model to identify and mitigate potential security threats, thereby enhancing the overall robustness and reliability of SDN systems. The study in [48] used the 5 GENSURE testbed to evaluate the security properties of data flows in 5G and beyond networks. The results provide insights into the effectiveness of the proposed framework in addressing the security challenges in network slices in multi-domain scenarios. The analysis of security properties helped to assess the framework's performance in dynamic network environments, demonstrating its practical applicability and effectiveness in 5G multi-domain scenarios.