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

Area of Science:

• Cybersecurity
• Network Security
• Aerospace Engineering

Background:

• Unmanned Aerial Vehicle (UAV) networks are crucial for the low-altitude economy but face significant security threats like node infiltration and data tampering.
• Current trust management schemes are limited by infrastructure dependence, inadequate multi-dimensional trust evaluation, and susceptibility to collusion attacks.

Purpose of the Study:

• To propose a novel Group Decision-Making (GDM)-enabled Dynamic Trust Management (DTM) method for low-altitude UAV networks.
• To enhance the security and reliability of UAV networks against malicious activities.

Main Methods:

• The proposed GDM-DTM method incorporates four core components: Subjective Consistency Evaluation, Objective Consistency Evaluation, Global Consistency Evaluation, and Self-Proof Consistency Evaluation.
• A Dynamic Trust Adjustment Mechanism with multi-attribute trust computation is integrated for infrastructure-independent trust evaluation and malicious UAV detection.

Main Results:

• GDM-DTM achieved 85.04% accuracy and an F-score of 91.66% with a 30% malicious node ratio.
• This represents a significant improvement over existing state-of-the-art methods, with accuracy increasing by 6.04% and F-score by 3.71%.

Conclusions:

• The GDM-DTM method offers an effective and robust solution for trust management in low-altitude UAV networks.
• The proposed approach enhances malicious UAV detection capabilities while reducing reliance on ground infrastructure.