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January 1, 2026International Journal of Sensor Networks

Stacked Ensemble Deep Learning for Trust Evaluation in Wireless Sensor Network Nodes

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Key Points

This research aims to develop a stacked ensemble deep learning model to assess trust in wireless sensor network nodes.
Developed a stacked ensemble deep learning architecture for trust evaluation.
Analyzed various sensor node data for accurate trust scoring.
Evaluated model performance through comparative analysis with existing methods.
Achieved a trust evaluation accuracy of 95% (95% CI 93-97%).
Showed improvement in trust assessment over traditional methods by a margin of 15%.
Resolved key security vulnerabilities associated with sensor networks.

Implication

Evaluates trust assessment in wireless sensor networks, suggesting enhanced security measures.

Abstract

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Cite This Study

Li Chen (2026) studied this question.

synapsesocial.com/papers/6a05680ea550a87e60a20764 https://doi.org/10.1504/ijsnet.2026.10078295

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