Topology-Stress-Based Wormhole Attack Defense for Power Wireless Sensor Networks with UWB Physical-Layer Awareness

Area of Science:

• Electrical Engineering
• Computer Science
• Network Security

Background:

• Power wireless sensor networks (PWSNs) are crucial for smart grids, but topology authenticity is vital for reliable communication.
• Wormhole attacks exploit low-latency tunnels to disrupt network topology and routing, posing a significant threat.
• Environmental factors like metallic obstructions and non-line-of-sight (NLOS) propagation complicate attack detection by mimicking topology distortion.

Purpose of the Study:

• To propose a robust wormhole attack defense method for PWSNs that addresses challenges posed by practical power environments.
• To enhance the reliability and stability of topology authenticity verification in PWSNs.
• To differentiate between normal ranging anomalies and malicious wormhole attacks.

Main Methods:

• Developed a topology-stress-based defense using ultra-wideband (UWB) physical-layer awareness.
• Extracted channel impulse response features (first-path power ratio, root-mean-square delay spread) to assess link-ranging reliability.
• Modeled network links as virtual springs to derive a topology stress indicator quantifying geometric inconsistency from forged links.
• Implemented a Beta-based temporal evidence fusion mechanism for graded node access decisions.

Main Results:

• The proposed method effectively suppresses false alarms caused by NLOS propagation while maintaining high sensitivity to wormhole attacks.
• Achieved more stable detection performance compared to baseline methods under varying ranging errors and attack intensities.
• Hardware experiments confirmed that topology stress can accurately distinguish between normal, NLOS-affected, and wormhole-attacked links.

Conclusions:

• The topology-stress-based method with UWB awareness provides effective and stable wormhole attack detection in PWSNs.
• The approach enhances topology authenticity verification, crucial for secure and reliable smart grid operations.
• This defense mechanism is resilient to environmental anomalies that can be mistaken for attacks.