Comparative Analysis of Detection Techniques for Malicious Node Identification in Wireless Sensor Networks

This research investigates the challenges of malicious node detection in Wireless Sensor Networks (WSNs). The study provides a comparative analysis of various detection techniques, including Trust-Based Mechanisms, Anomaly Detection, Reputation-Based Systems, Intrusion Detection Systems (IDS), Energy-Based Detection, and Hybrid Approaches. Each technique is evaluated based on its description, advantages, disadvantages, and common applications. The analysis highlights the tradeoffs between resource efficiency and detection accuracy, underscoring the need for adaptive and lightweight solutions to address the unique challenges of WSN security. This research provides valuable insights into the development of robust and secure WSNs, enabling their effective deployment in critical applications.