Mobile WSN Wormhole Attack Without Beacon Node Localization Based on GNDO Algorithm
Yongqin Zhu, Jingjing Zhu · Security and Privacy · 2025
ABSTRACT A wireless sensor network (WSN) accomplishes its objectives through the coordinated efforts of numerous specially designed sensor nodes positioned within the monitored area. But some protocols choose the path with the least hops or the strongest signal strength as the preferred path for data transmission; attackers can quickly forward packets from one area to another through wormhole links. However, due to the fast movement speed of sensing nodes, traditional techniques based on arrival time are based on the known position relationships between nodes, but it is difficult to obtain node positions based on the strength of the received signals from unknown nodes, resulting in low positioning accuracy. Therefore, this article focuses on the problem of beacon‐free node localization in mobile WSNs under wormhole attacks. Based on the basic structure of sensor nodes, a global mobile WSN model represented by a state transition equation is constructed. Nodes are flagged as suspicious if their number of neighbors surpasses a specific threshold, and the reference path hop count between proprietary neighbor nodes is calculated. A path trust evaluation metric is derived by integrating both direct and indirect trust to formulate a trust model, thereby detecting wormhole attacks in the path. In response to the situation where wormhole attacks damage the network topology, RSSI technology is introduced to convert the received signal strength into the distance between nodes, and the localization problem is transformed into an unconstrained minimum square error problem. The Generalized Normal Distribution Optimization (GNDO) algorithm is employed to optimize and find the solution to the objective function, and the optimal position solution of the beacon‐free node under wormhole attacks is finally output to solve the problem of difficult‐to‐obtain attack node position based on unknown nodes. The experimental outcomes demonstrate that our approach achieves a remarkably low detection error rate of 0.13 for identifying network wormhole attacks, and the positioning accuracy is between 95% and 98%. The highest F1 value for beacon‐free node positioning is 0.98.