Performance Evaluation of Localization Accuracy for a Log-Normal Shadow Fading Wireless Sensor Network under Physical...

Area of Science:

• Wireless Sensor Networks
• Localization Algorithms
• Cybersecurity in IoT

Background:

• Accurate localization is critical for wireless sensor networks (WSNs).
• Physical barrier attacks pose a significant threat to WSN localization accuracy, particularly for range-based methods like Received Signal Strength Indication (RSSI).
• These attacks introduce location estimation errors by disrupting signal propagation.

Purpose of the Study:

• To develop a robust and accurate localization technique for WSNs against physical barrier attacks.
• To enhance the performance of RSS-based localization under adverse conditions, including signal fading and adversarial attacks.
• To introduce a method for detecting and mitigating attack-prone regions within the WSN.

Main Methods:

• Proposed a hybrid localization approach combining multi-frequency multi-power localization (C-MFMPL) and step function multi-frequency multi-power localization (SF-MFMPL).
• Integrated fingerprint matching and lateration techniques for improved location estimation.
• Developed a grid coloring algorithm to identify signal hole maps, indicating regions vulnerable to attacks.

Main Results:

• Demonstrated enhanced and robust RSS localization performance.
• Successfully detected, filtered, and eliminated the effects of physical barrier attacks.
• Showed improved accuracy despite log-normal shadow fading effects.

Conclusions:

• The proposed C-MFMPL and SF-MFMPL localization technique offers significant robustness against physical barrier attacks in WSNs.
• The grid coloring algorithm effectively identifies attack-prone areas, enabling targeted mitigation strategies.
• The approach enhances the reliability of RSS-based localization in challenging environments.