A Genetic Algorithm with a Trust Model Function for Detecting Sinkhole and Wormhole Nodes in Wireless Sensor Networks

Authors

  • Rafiw Seidu C. K. Tedam University of Technology and Applied Sciences, School of Computing and Information Sciences, Department of Information Systems and Technology, Upper East Region, Navrongo, Ghana
  • Abdul-Mumin Selanwiah Salifu C. K. Tedam University of Technology and Applied Sciences, School of Computing and Information Sciences, Department of Information Systems and Technology, Upper East Region, Navrongo, Ghana
  • Johnbosco A. K. Ansuura C. K. Tedam University of Technology and Applied Sciences, School of Computing and Information Sciences, Department of Information Systems and Technology, Upper East Region, Navrongo, Ghana

DOI:

https://doi.org/10.14738/tecs.124.17242

Keywords:

Genetic algorithm, Trust model, Sinkhole node, Wormhole node

Abstract

This study delved into wireless sensor networks, comprising numerous nodes with limited energy, computation, and transmission capabilities. Wireless sensor networks face security challenges due to their vulnerability to capture and compromise in insecure environments. Malicious nodes exploit communication's wireless nature, engaging in sinkhole and wormhole attacks. To address this, we propose a genetic strategy utilising a trust-based formula as a fitness function to evaluate sensor node reliability. Nodes progressing beyond a trust threshold criterion are identified, isolating malicious nodes responsible for attacks. Implemented in MATLAB 2018a, our approach effectively identifies and isolates such nodes, as demonstrated by the results.

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Published

2024-07-24

How to Cite

Seidu, R., Salifu, A.-M. S., & Ansuura, J. A. K. (2024). A Genetic Algorithm with a Trust Model Function for Detecting Sinkhole and Wormhole Nodes in Wireless Sensor Networks. Transactions on Engineering and Computing Sciences, 12(4), 30–44. https://doi.org/10.14738/tecs.124.17242