DÏoT: A Federated Self-learning Anomaly Detection System for IoT

IoT devices are increasingly deployed in daily life. Many of these devices are, however, vulnerable due to insecure design, implementation, and configuration. As a result, many networks already have vulnerable IoT devices that are easy to compromise. This has led to a new category of malware specifi...

Ausführliche Beschreibung

Bibliographische Detailangaben

Veröffentlicht in:	Proceedings of the International Conference on Distributed Computing Systems S. 756 - 767
Hauptverfasser:	Nguyen, Thien Duc, Marchal, Samuel, Miettinen, Markus, Fereidooni, Hossein, Asokan, N., Sadeghi, Ahmad-Reza
Format:	Tagungsbericht
Sprache:	Englisch
Veröffentlicht:	IEEE 01.07.2019
Schlagworte:	Anomaly detection Data models federated deep learning Internet of Things IoT malware IoT security Logic gates Malware Monitoring Security self-learning
ISSN:	2575-8411
Online-Zugang:	Volltext
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!