Research Article

Integrated Clustering-based Approach for Energy Efficient base Station Placement Strategy in Learning Wireless Sensor Intrusion Detection System

Authors

  • Seyyed Esmaeil Najafi * Department of Industrial Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran.
  • Duško Tešić University of Defence in Belgrade, Belgrade, Serbia.
  • Mingyue Wang School of Computer and Information, Lanzhou University of Technology, China.

https://doi.org/10.48314/ceti.v1i4.40

Abstract

Wireless Sensor Networks (WSN) are becoming more popular with the advent of Internet of Things (IoT) applications in recent years. Enormous applications in Business, Government, Research and Personal applications use WSNs. Though WSNs are beneficiary, security issues prevailing in WSNs pose challenges in various aspects due to the limitation of Resources. Due to unmatured security features, Intrusion in WSNs is common. Several Intrusion Detection Systems (IDS) are in use for WSNs, but they need to be improved for robustness, reliability, trustworthiness and Energy Efficiency (EE). This paper proposes a technique for Energy Efficient Base Station Placement (BSP) for Learning based IDS using an Integrated and Clustering Approach.

Keywords

Wireless sensor networks Energy efficiency Base station placement Intrusion detection system Machine learning
References (11)
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How to Cite

Najafi, S. E., Tešić, D., & Wang, M. (2024). Integrated Clustering-based Approach for Energy Efficient base Station Placement Strategy in Learning Wireless Sensor Intrusion Detection System. Computational Engineering and Technology Innovations, 1(4), 194-201. https://doi.org/10.48314/ceti.v1i4.40

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