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Robust multiple frequency multiple power localization schemes in the presence of multiple jamming attacks.
Ahmed Abdulqader Hussein1,2, Chee Yen Leow1, Tharek A Rahman1
1Wireless Communication Centre (WCC), Faculty of Electrical Engineering, Universiti Teknologi Malaysia, UTM Skudai, Johor 81310, Malaysia.
Plos One
|May 12, 2017
Summary
This study introduces new localization algorithms to combat jamming attacks in wireless sensor networks. The methods enhance positioning accuracy despite interference, improving network reliability.
Area of Science:
- Computer Science
- Electrical Engineering
- Network Security
Background:
- Wireless sensor network (WSN) localization is critical but vulnerable to jamming attacks.
- Jamming significantly degrades localization accuracy by disrupting communication and affecting Received Signal Strength (RSS).
Purpose of the Study:
- To propose and evaluate novel algorithms for robust WSN localization against diverse jamming attacks.
- To mitigate the impact of jamming on RSS-based localization techniques.
Main Methods:
- Development of Combination Multiple Frequency Multiple Power Localization (C-MFMPL) and Step Function Multiple Frequency Multiple Power Localization (SF-MFMPL) algorithms.
- Utilizing dual-frequency anchor nodes for averaged RSS readings to counter random and constant jammers.
- Implementing a three-stage filtering system to address capture and replay jamming attacks.
Main Results:
- Proposed algorithms demonstrate robust localization performance under various jamming scenarios (capture/replay, random, constant).
- Performance comparison between ideal conditions and jamming-attacked environments highlights the effectiveness of the proposed methods.
- Validation under a log-normal shadow fading propagation model.
Conclusions:
- The developed C-MFMPL and SF-MFMPL algorithms effectively enhance localization robustness in WSNs facing multiple jamming threats.
- The proposed techniques provide a reliable solution for accurate sensor node positioning in challenging, interference-prone environments.
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