"Toward Secure IoT Infrastructure: Integrating Zero Trust, Federated Learning, and Dynamic Trust Management Models"

Abstract

With the proliferation of Internet of Things (IoT) devices across industrial, healthcare, and consumer domains, the demand for secure, scalable, and intelligent infrastructure has surged. This paper presents an in-depth synthesis of 29 high-impact research contributions focusing on the integration of Zero Trust architectures, Federated Learning, and Dynamic Trust Management Models for securing IoT ecosystems. The study categorizes key themes including cybersecurity frameworks, AI-augmented anomaly detection, edge computing optimization, and AI-driven software development. By analyzing the convergence of AI with decentralized architectures and trustless communication, we highlight how hybrid deep learning frameworks, blockchain, and quantum computing are reshaping security paradigms. Graphical analysis of research trends across thematic areas and author contributions is also provided. The findings reinforce that the fusion of intelligent diagnostics with resilient trust frameworks offers a foundational blueprint for the future of secure digital ecosystems.