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Related Experiment Video

Updated: May 25, 2025

A Tactile Automated Passive-Finger Stimulator TAPS
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Adaptive Trust Evaluation Model Based on Entropy Weight Method for Sensing Terminal Process.

Tao Li1,2,3, Yanyi Zhang1

  • 1School of Cyber Science and Engineering, Southeast University, Nanjing 211189, China.

Entropy (Basel, Switzerland)
|February 26, 2025
PubMed
Summary
This summary is machine-generated.

This study introduces PB-ATEM, an adaptive trust evaluation model for remote sensing (RS) terminals. It enhances detection accuracy and malicious process identification by combining direct and reciprocal trust values.

Keywords:
auto-correlationentropy weight methodk-means cluster analysisprocess securitytrust evaluationtrust value

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Area of Science:

  • Computer Science
  • Information Security
  • Remote Sensing

Background:

  • Remote sensing (RS) terminals are vulnerable to attacks due to their unattended nature.
  • Existing trust evaluation models for RS sensing terminals suffer from low performance and precision in detecting malicious processes.

Purpose of the Study:

  • To propose an adaptive trust evaluation model (PB-ATEM) for sensing terminal processes.
  • To enhance the accuracy and speed of identifying malicious processes in remote sensing systems.

Main Methods:

  • Developed PB-ATEM using the entropy weight method and k-means clustering.
  • Incorporated direct trust (dynamic auto-correlation, reward/punishment) and reciprocal trust values.
  • Weighted direct and reciprocal trust values for an integrated trust score.

Main Results:

  • PB-ATEM demonstrates rapid response to malicious processes.
  • The proposed model achieves higher detection accuracy compared to existing methods.
  • PB-ATEM shows improved capability in identifying malicious sensing terminal processes.

Conclusions:

  • PB-ATEM offers a more effective solution for trust evaluation in remote sensing terminals.
  • The model's adaptive nature and combined trust metrics enhance security against malicious activities.
  • This approach significantly improves the reliability and security of unattended remote sensing systems.