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Open access 2026

Lightweight AI-Based Threat Detection and Surveillance Secure Edge-IoT Healthcare Systems

Simulation results confirm that the proposed framework achieves improvements in energy overhead, latency, throughput, and response time compared to the RePUF-IoT and AIBS-IoTH schemes.

Menwa Alshammeri, Khalid Haseeb, Mamoona Humayun et al. · 0 citations
Review Open access Aug 2026

AI-ENHANCED INFORMATION SECURITY FRAMEWORKS FOR CLOUD-ENABLED IOT NETWORKS: A COMPREHENSIVE REVIEW

This review paper critically examines the integration of Artificial Intelligence (AI) and Machine Learning (ML) techniques to enhance information security within Cloud-IoT networks, focusing on hybrid Deep Learning models (CNN-LSTM), predictive analytics, and automated threat response mechanisms.

R. Saravanakumar, V.Anuratha, M.Elamparithi · 0 citations
Review 2026

Federated Learning in Fog Computing Within IoT Environments: An Up-to-Date and Comprehensive Survey

The Internet of Things (IoT) connects diverse, resource-constrained devices, driving innovation in domains such as healthcare, smart cities, and industrial automation. However, the exponential growth of IoT devices poses critical challenges in data processing, privacy, security, and latency. Fog Computing (FC) mitigate...

Ahmed Rjiba, Hicham Lakhlef, Joachim Bruneau-Queyreix et al. · 0 citations
#generative ai Review Open access Sep 2026

Generative Artificial Intelligence for Smart IoT Systems: A Comprehensive Review

This review presents a comprehensive analysis of GenAI-enabled IoT architectures, including edge-cloud, federated, and autonomous approaches, as well as opportunities in model compression, runtime optimization, and edge-cloud collaboration.

Bal Krishna Sharma · 0 citations
Open access Sep 2026

AI-Driven Vulnerability Management Framework for the Internet of Things

This study proposes an AI driven vulnerability management framework that integrates anomaly detection techniques using machine learning to enhance proactive threat identification and mitigation in IoT ecosystems, and demonstrates that AI based models significantly outperform traditional methods in detecting previously...

Daniel Nafisatu Mshelbila · 0 citations

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