GDM-DTM: A Group Decision-Making-Enabled Dynamic Trust Management Method for Malicious Node Detection in Low-Altitude UAV Networks

Hu, Yabao; Gan, Yulong; Wu, Haoyu; Wang, Cong; Ma, Maode; Xiong, Cheng

doi:10.3390/s25133982

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GDM-DTM: A Group Decision-Making-Enabled Dynamic Trust Management Method for Malicious Node Detection in Low-Altitude UAV Networks

by

Yabao Hu

¹,

Yulong Gan

¹,

Haoyu Wu

¹,

Cong Wang

¹,

Maode Ma

^2,*

and

Cheng Xiong

¹

College of Artificial Intelligence, Tianjin University of Science and Technology, Tianjin 300457, China

²

College of Engineering, Qatar University, Doha P.O. Box 2713, Qatar

^*

Author to whom correspondence should be addressed.

Sensors 2025, 25(13), 3982; https://doi.org/10.3390/s25133982

Submission received: 6 May 2025 / Revised: 15 June 2025 / Accepted: 25 June 2025 / Published: 26 June 2025

(This article belongs to the Special Issue Intelligence, Security, Trust and Privacy Advances in IoT, Bigdata and 5G Networks (2nd Edition))

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Abstract

As a core enabler of the emerging low-altitude economy, UAV networks face significant security risks during operation, including malicious node infiltration and data tampering. Existing trust management schemes suffer from deficiencies such as strong reliance on infrastructure, insufficient capability for multi-dimensional trust evaluation, and vulnerability to collusion attacks. To address these issues, this paper proposes a group decision-making (GDM)-enabled dynamic trust management method, termed GDM-DTM, for low-altitude UAV networks. GDM-DTM comprises four core parts: Subjective Consistency Evaluation, Objective Consistency Evaluation, Global Consistency Evaluation, and Self-Proof Consistency Evaluation. Furthermore, the method integrates a Dynamic Trust Adjustment Mechanism with multi-attribute trust computation, enabling efficient trust evaluation independent of ground infrastructure and thereby facilitating effective malicious UAV detection. The experimental results demonstrate that under identical conditions with a malicious node ratio of 30%, GDM-DTM achieves an accuracy of 85.04% and an F-score of 91.66%. Compared to the current state-of-the-art methods, this represents an improvement of 6.04 percentage points in accuracy and 3.71 percentage points in F-score.

Keywords: trust management; group decision-making; UAV network; low-altitude economy

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MDPI and ACS Style

Hu, Y.; Gan, Y.; Wu, H.; Wang, C.; Ma, M.; Xiong, C. GDM-DTM: A Group Decision-Making-Enabled Dynamic Trust Management Method for Malicious Node Detection in Low-Altitude UAV Networks. Sensors 2025, 25, 3982. https://doi.org/10.3390/s25133982

AMA Style

Hu Y, Gan Y, Wu H, Wang C, Ma M, Xiong C. GDM-DTM: A Group Decision-Making-Enabled Dynamic Trust Management Method for Malicious Node Detection in Low-Altitude UAV Networks. Sensors. 2025; 25(13):3982. https://doi.org/10.3390/s25133982

Chicago/Turabian Style

Hu, Yabao, Yulong Gan, Haoyu Wu, Cong Wang, Maode Ma, and Cheng Xiong. 2025. "GDM-DTM: A Group Decision-Making-Enabled Dynamic Trust Management Method for Malicious Node Detection in Low-Altitude UAV Networks" Sensors 25, no. 13: 3982. https://doi.org/10.3390/s25133982

APA Style

Hu, Y., Gan, Y., Wu, H., Wang, C., Ma, M., & Xiong, C. (2025). GDM-DTM: A Group Decision-Making-Enabled Dynamic Trust Management Method for Malicious Node Detection in Low-Altitude UAV Networks. Sensors, 25(13), 3982. https://doi.org/10.3390/s25133982

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GDM-DTM: A Group Decision-Making-Enabled Dynamic Trust Management Method for Malicious Node Detection in Low-Altitude UAV Networks

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