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

Area of Science:

• Computer Science
• Cybersecurity
• Artificial Intelligence

Background:

• The Financial Internet of Things (FIoT) faces significant security threats due to vulnerable intelligent devices.
• Limited resources and AI deployment in FIoT can compromise system availability.
• Malicious attacks pose substantial risks to FIoT stability and security.

Purpose of the Study:

• To propose a trust-based collaborative smart device selection algorithm for FIoT.
• To enhance resistance against malicious behaviors and attacks in FIoT environments.
• To address resource allocation challenges for trusted devices under constrained edge resources.

Main Methods:

• Developed a trust-based algorithm integrating subjective/objective trust, dynamic blacklists/whitelists, domain knowledge, and game theory.
• Implemented real-time dynamic trust level evaluation and a transformation mechanism for blacklists/whitelists.
• Proposed a coalition game-based algorithm for resource allocation considering device activity and trust levels.

Main Results:

• The proposed algorithm significantly improves anti-attack capabilities in FIoT smart devices.
• Maintained high task success rates in both single and complex attack scenarios.
• Demonstrated superior task success rates and resource allocation performance compared to existing methods.

Conclusions:

• The trust-based collaborative device selection algorithm effectively enhances FIoT security and reliability.
• The integrated approach of adaptive trust evaluation and dynamic lists improves device trustworthiness.
• The coalition game-based resource allocation is efficient for trusted devices in constrained environments.