Local Trust in Internet of Things Based on Contract Theory

Area of Science:

• Computer Science
• Network Security
• Artificial Intelligence

Background:

• Internet of Things (IoT) networks require secure, authenticated channels for cooperative functioning.
• Establishing trust in large, dynamic, and heterogeneous IoT networks is challenging.
• Existing mechanisms struggle with fluctuating node participation and incomplete information.

Purpose of the Study:

• To develop an autonomous trust mechanism for secure communication in IoT ecosystems.
• To leverage network economics and crowd-sourcing for establishing trust between nodes.
• To incentivize accurate trust reporting and authentication efforts among participating nodes.

Main Methods:

• A contract-theoretic framework utilizing network economics principles.
• Stochastic Learning Automata for node selection based on network and social metrics.
• Bayesian trust belief distributions derived from historical node behavior.
• An effort-reward model to incentivize node participation and accurate reporting.

Main Results:

• The proposed framework converges to an optimal trust solution autonomously.
• Achieved near-optimal performance despite incomplete information and malicious nodes.
• Maximized overall social welfare, outperforming existing state-of-the-art methods.

Conclusions:

• The contract-theoretic framework provides an effective, autonomous solution for IoT trust.
• Crowd-sourced trust based on neighbor efforts enhances network security and cooperation.
• The approach demonstrates robustness against incomplete information and adversarial behavior.