Machine Learning-Based Network Vulnerability Analysis of Industrial Internet of Things

It is critical to secure the Industrial Internet of Things (IIoT) devices because of potentially devastating consequences in case of an attack. Machine learning (ML) and big data analytics are the two powerful leverages for analyzing and securing the Internet of Things (IoT) technology. By extension...

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Veröffentlicht in:	IEEE internet of things journal Jg. 6; H. 4; S. 6822 - 6834
Hauptverfasser:	Zolanvari, Maede, Teixeira, Marcio A., Gupta, Lav, Khan, Khaled M., Jain, Raj
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Piscataway IEEE 01.08.2019 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Analytics Anomalies Artificial intelligence Cyber attack Cybersecurity Electromagnetic interference Industrial applications Industrial Internet of Things Industrial Internet of Things (IIoT) Internet of Things intrusion detection Intrusion detection systems Literature reviews Machine learning machine learning (ML) network security Protocol (computers) Query languages Structured Query Language-SQL supervisory control and data acquisition (SCADA) Vulnerability vulnerability assessment
ISSN:	2327-4662, 2327-4662
Online-Zugang:	Volltext
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