Constructing a Dynamic Trust Assessment Mechanism Combining Zero Knowledge Proof with Unsupervised Learning

Nai-Wei Lo¹, Cheng-I Lin², Chih-Chieh Chang^3,*, Chi-Yang Chang⁴, Tran Thi Luu Ly¹
1 Department of Information Management, National Taiwan University of Science and Technology, Taipei, Taiwan
2 Graduate Institute of Management, National Taiwan University of Science and Technology, Taipei, Taiwan
3 School of Management, National Taiwan University of Science and Technology, Taipei, Taiwan
4 Graduate Institute of A.I. Cross-Disciplinary Technology, National Taiwan University of Science and Technology, Taipei, Taiwan
* Corresponding Author: Chih-Chieh Chang. Email: email
(This article belongs to the Special Issue: Machine learning and Blockchain for AIoT: Robustness, Privacy, Trust and Security)

Computer Modeling in Engineering & Sciences https://doi.org/10.32604/cmes.2026.077316

Received 06 December 2025; Accepted 24 February 2026; Published online 09 April 2026

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Abstract

The growing frequency of malicious attacks on Internet of Things (IoT) devices has rendered conventional approaches with static label-dependent risk assessment models obsolete, especially when coping with unknown and continuously evolving threats. To mitigate these challenges, a novel dynamic trust evaluation framework approach is proposed in this work. The proposed framework utilized unsupervised learning and zero-knowledge proofs to assess device risks in complex environments adaptively, with an accuracy rate of 98.96% for normal clustering and 95.39% for anomalies. K-means clustering algorithm is leveraged to distinguish risk patterns with an additional Decision Tree classification algorithm to analyze the distinguishing characteristics of the behaviors of normal and anomalous devices. The architecture is evaluated in a simulated environment based on real device interaction, with various malicious attacks proportions. In addition, Zero Trust Architecture is integrated into this novel framework to ensure no implicit trust exists between devices, which enforces trust assessment before any collaboration or data exchange.