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Article

A Method for Trust-Based Collaborative Smart Device Selection and Resource Allocation in the Financial Internet of Things

1
School of Applied Technology, University of Science and Technology Liaoning, Anshan 114051, China
2
Julong Co., Ltd., Anshan 114051, China
3
School of Computer Science and Technology, Dalian University of Technology, Dalian 116024, China
4
School of Electronic and Information Engineering, University of Science and Technology Liaoning, Anshan 114051, China
*
Author to whom correspondence should be addressed.
Sensors 2025, 25(13), 4082; https://doi.org/10.3390/s25134082
Submission received: 3 June 2025 / Revised: 28 June 2025 / Accepted: 29 June 2025 / Published: 30 June 2025
(This article belongs to the Special Issue Network Security and IoT Security: 2nd Edition)

Abstract

With the rapid development of the Financial Internet of Things (FIoT), many intelligent devices have been deployed in various business scenarios. Due to the unique characteristics of these devices, they are highly vulnerable to malicious attacks, posing significant threats to the system’s stability and security. Moreover, the limited resources available in the FIoT, combined with the extensive deployment of AI algorithms, can significantly reduce overall system availability. To address the challenge of resisting malicious behaviors and attacks in the FIoT, this paper proposes a trust-based collaborative smart device selection algorithm that integrates both subjective and objective trust mechanisms with dynamic blacklists and whitelists, leveraging domain knowledge and game theory. It is essential to evaluate real-time dynamic trust levels during system execution to accurately assess device trustworthiness. A dynamic blacklist and whitelist transformation mechanism is also proposed to capture the evolving behavior of collaborative service devices and update the lists accordingly. The proposed algorithm enhances the anti-attack capabilities of smart devices in the FIoT by combining adaptive trust evaluation with blacklist and whitelist strategies. It maintains a high task success rate in both single and complex attack scenarios. Furthermore, to address the challenge of resource allocation for trusted smart devices under constrained edge resources, a coalition game-based algorithm is proposed that considers both device activity and trust levels. Experimental results demonstrate that the proposed method significantly improves task success rates and resource allocation performance compared to existing approaches.
Keywords: Financial Internet of Things; edge computing; trust evaluation; resource allocation; coalition game Financial Internet of Things; edge computing; trust evaluation; resource allocation; coalition game

Share and Cite

MDPI and ACS Style

Wang, B.; Wang, J.; Li, M. A Method for Trust-Based Collaborative Smart Device Selection and Resource Allocation in the Financial Internet of Things. Sensors 2025, 25, 4082. https://doi.org/10.3390/s25134082

AMA Style

Wang B, Wang J, Li M. A Method for Trust-Based Collaborative Smart Device Selection and Resource Allocation in the Financial Internet of Things. Sensors. 2025; 25(13):4082. https://doi.org/10.3390/s25134082

Chicago/Turabian Style

Wang, Bo, Jiesheng Wang, and Mingchu Li. 2025. "A Method for Trust-Based Collaborative Smart Device Selection and Resource Allocation in the Financial Internet of Things" Sensors 25, no. 13: 4082. https://doi.org/10.3390/s25134082

APA Style

Wang, B., Wang, J., & Li, M. (2025). A Method for Trust-Based Collaborative Smart Device Selection and Resource Allocation in the Financial Internet of Things. Sensors, 25(13), 4082. https://doi.org/10.3390/s25134082

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