Skip to content
Log in
Sponsored Artificial Intelligence: A Modern Approach, Global Edition Artificial Intelligence: A Modern Approach, Global Edition

Similar papers

Sep 2026

SHFL-EI: Secure Hierarchical Federated Learning with Edge Intelligence for Robust IoT Security

The rapid proliferation of Internet of Things (IoT) systems has significantly increased the attack surface of modern cyber-physical infrastructures, creating the need for scalable, intelligent, and privacy-preserving security solutions. Traditional centralized intrusion detection approaches are limited by high communic...

Afef Slimani, K. Karoui · 0 citations
Sep 2026

Federated Learning Based Anamoly Detection for Secure and Resilient Internet of Things Communication Network

The rapid proliferation of Internet of Things (IoT) devices has created highly distributed communication environments that are increasingly exposed to anomalous traffic, botnet activity, denial-of-service attacks, spoofing, malware propagation, and other cyber threats. Conventional centralized intrusion detection appro...

Salman Arafath Mohammed · 0 citations
#federated learning Open access Aug 2026

Privacy-Enhancing Federated Learning Models for Cybersecurity in IoT Networks

Federated Learning is investigated as a decentralized approach to intrusion detection that enables local model training on IoT edge devices while transmitting only encrypted model updates to a central server, thereby preserving data privacy and reducing communication overhead.

Mohammed Ajuji, Y. M. Malgwi, A. Ahmadu et al. · 0 citations
Conference Open access 2026

Scalable and Efficient Security Solutions for IoT Networks: An Adaptive Machine Learning Approach

The number of Internet of Things (IoT) devices has grown at a rapid pace and has created a larger attack surface for modern networks, making them an appealing target for botnets, ransomware, and distributed denial-of-service (DDoS) attacks. While traditional IDSs are typically built with a centralized machine learning...

J. J. Patil, Prajakta P. Shirke · 0 citations
#graph neural networks Open access Oct 2026

Trust-Aware Federated Learning for Privacy-Preserving IoT Intrusion Detection

FLZT-IDS (Federated Learning with Zero-Trust for Intrusion Detection in IoT) employs gradient-deviation monitoring to mitigate the effects of heterogeneous client updates, while Graph Neural Networks and an Attention-based BiLSTM capture relational and temporal attack patterns.

Santosh Kumar Banbhrani, Chengyongxiao Wei, Muhammad Asad · 0 citations
Open access Sep 2026

Edge Computing-Enabled Secure Federated Learning for Anomaly Detection in Industrial IoT Sensor Streams

A federated learning framework to collaboratively develop an anomaly detection model from multiple edge nodes, without sharing the raw sensor data, so that data sovereignty is preserved, and demonstrates that practical, deployable security for federated learning in IIoT is achievable without sacrificing accuracy or res...

Wijdan Noaman Marzoog Al Mukhtar · 0 citations

We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.