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Updated: May 25, 2026

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit
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Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit

Published on: September 8, 2023

A trust evaluation algorithm for wireless sensor networks based on node behaviors and D-S evidence theory.

Renjian Feng1, Xiaofeng Xu, Xiang Zhou

  • 1School of Instrument Science and Opto-electronics Engineering, Beijing University of Aeronautics and Astronautics (Beihang University), Beijing 100191, China. rjfeng@buaa.edu.cn

Sensors (Basel, Switzerland)
|February 10, 2012
PubMed
Summary

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A new algorithm, Node Behavioral Strategies Banding Belief Theory of the Trust Evaluation Algorithm (NBBTE), enhances wireless sensor network security. NBBTE effectively identifies malicious nodes by analyzing their behavior, improving overall network trust.

Area of Science:

  • Computer Science
  • Network Security
  • Wireless Sensor Networks

Background:

  • Wireless sensor networks (WSNs) face significant security vulnerabilities due to environmental exposure and interference.
  • Compromised sensor nodes pose a threat to network integrity and data reliability.

Purpose of the Study:

  • To propose a novel trust evaluation algorithm, NBBTE, for enhancing WSN security.
  • To effectively identify and mitigate malicious nodes within WSNs.

Main Methods:

  • Integrated node behavioral strategies with modified evidence theory for trust evaluation.
  • Calculated direct and indirect trust values using weighted averages of established trust factors.
  • Applied fuzzy set method and revised D-S evidence combination rule to synthesize integrated trust values.
Keywords:
evidence theorynetwork securitynode behaviorstrust evaluationwireless sensor networks

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Last Updated: May 25, 2026

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit
05:30

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit

Published on: September 8, 2023

Main Results:

  • NBBTE effectively identifies malicious nodes in WSNs.
  • The algorithm demonstrates the 'hard to acquire, easy to lose' characteristic of trust.
  • NBBTE excels at illustrating the distinct contributions of individual nodes to trust evaluation.

Conclusions:

  • The proposed NBBTE algorithm significantly improves WSN security against malicious attacks.
  • NBBTE provides a robust framework for dynamic trust assessment in decentralized networks.
  • The algorithm's ability to differentiate node contributions enhances transparency and accountability.