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

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.

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-04-25
DOI
https://doi.org/10.5281/zenodo.15281301
Primary Topic
IoT and Edge/Fog Computing
Type
article
Field-Weighted Citation Impact
0.00
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article

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

Zenodo (CERN European Organization for Nuclear Research)
IoT and Edge/Fog Computing
article

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

article en

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.

Zenodo (CERN European Organization for Nuclear Research)
Industry, innovation and infrastructure
Openalex Percentile: Top 48%
IoT and Edge/Fog Computing
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Toward Secure IoT Infrastructure: Integrating Zero Trust, Federated Learning, and Dynamic Trust Management Models · Zenodo (CERN European Organization for Nuclear Research) (2025) | TGRS Research Map | TGRS