Research on Provenance Issues and Management in Wireless Sensor Networks (WSNs) focuses on ensuring the trustworthiness, accountability, and integrity of sensor data as it travels from source nodes to the base station. Data provenance captures the origin, transmission path, and transformation history of packets, which is essential for detecting false data injection, node compromise, and routing attacks. However, maintaining provenance in WSNs is challenging due to limited bandwidth, storage, and energy resources. Recent studies propose lightweight and secure provenance schemes using Bloom filters, probabilistic encoding, and cryptographic compression to reduce overhead while preserving traceability. Some works also integrate blockchain, distributed ledger, and machine learning-based provenance validation to enhance tamper-resistance and trust management. Overall, efficient provenance management is crucial for improving data reliability, security, and auditability in resource-constrained WSN environments.