Recent research in trust and reputation-based approaches for Wireless Sensor Networks focuses on designing lightweight and adaptive frameworks that assess the reliability of sensor nodes based on behavior, communication, and data integrity. These approaches utilize fuzzy logic, Bayesian inference, and machine learning to dynamically evaluate node trustworthiness, detect malicious activity, and ensure secure data transmission. Reputation-based models promote cooperative behavior among nodes while minimizing energy consumption and communication overhead. Overall, these studies enhance network resilience, improve data accuracy, and extend the operational lifetime of WSNs by integrating security intelligence into distributed trust management mechanisms.