Akademik Veri Yönetim Sistemi
MATHEMATICS, cilt.14, sa.6, 2026 (SCI-Expanded, Scopus)
Wireless sensor networks (WSNs) are highly susceptible to Denial-of-Service (DoS) attacks due to their resource-constrained and distributed nature. In this study, we propose a novel trust-based malicious node detection mechanism that leverages a Depth-First Search (DFS) strategy to trace and identify attack sources within clustered WSN architectures efficiently. The proposed approach dynamically evaluates trust scores between nodes to detect anomalous behaviors and employs a honeypot-based redirection system to isolate compromised nodes from the main communication flow. This combination enhances detection accuracy while minimizing false positives and energy overhead. The method is implemented and evaluated using a custom simulation environment. Comparative experimental results against state-of-the-art techniques such as the Evolved Trust Updating Mechanism (EVO) and Multi-agent Trust-based Intrusion Detection System (MULTI) demonstrate that our Trust-Based Honeypot (TBHP) achieves superior performance in terms of detection rate, false-alarm rate, and network lifetime extension.