Implementation of an Artificial Intelligence learning-based trust management system in social Internet of Things

Artificial intelligence, or AI, has been employed to raise the credibility ratings in trust management. In order to evaluate, quantify, and improve the trustworthiness of devices and organisations in the SIoT ecosystem, this study concentrates on creating a complete and adaptive trust management approach. In order to calculate trust scores for specific entities inside the network, the suggested uses ML algorithms and statistical models to examine a wide range of data sources, comprising device behaviour, user interactions, and contextual information. Data gathering, trust calculation, and trust adaption are the main elements of the AI-based trust management system. To build a knowledge base for the AI model, data from various sources are first gathered. In conclusion, implementing a trust management system with an AI learning foundation in the SIoT is a big step towards protecting and improving the SIoT ecosystem.