Recent research on Trust-Based Routing in Wireless Sensor Networks (WSNs) emphasizes enhancing network reliability, data integrity, and security against malicious nodes through intelligent trust management mechanisms. Modern approaches integrate trust computation models based on direct and indirect observations, energy consumption, and node behavior metrics such as packet forwarding ratio and communication frequency. Hybrid methods combining fuzzy logic, blockchain, and machine learning techniques have been developed to dynamically assess node trustworthiness, thereby improving route selection and network resilience. Trust-based protocols like Fuzzy Trust-based Secure Routing and Energy-aware Trust Routing optimize both security and energy efficiency, ensuring reliable data delivery while mitigating insider attacks and node misbehavior. These studies collectively demonstrate that adaptive and context-aware trust evaluation significantly strengthens secure communication in dynamic and large-scale WSN environments.