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Title: A Secure Network Model Against Bot Attacks in Edge-Enabled Industrial Internet of Things
Authors: Memos, Vasileios A.
Psannis, Konstantinos E.
Lv, Zhihan
Type: Article
Subjects: FRASCATI::Engineering and technology::Electrical engineering, Electronic engineering, Information engineering
FRASCATI::Engineering and technology::Mechanical engineering
FRASCATI::Engineering and technology::Other engineering and technologies
FRASCATI::Natural sciences::Computer and information sciences
Keywords: Botnets
distributed-denial-of-service (DDoS) attacks
Industry 4.0
Internet of Things (IoTs)
man-in-the-middle (MitM) attacks
Issue Date: 2022
Publisher: IEEE
Source: IEEE Transactions on Industrial Informatics
Volume: 18
Issue: 11
First Page: 7998
Last Page: 8006
Abstract: The new Industry 4.0 standard has offered many advantages to the industries improving their production rate since it evaluates novel cutting-edge technologies like artificial intelligence, machine learning, cyber-physical systems, and Internet of Things (IoTs) to automate manufacturing processes so as to minimize time and economical costs while improving the quality of products. However, this rapid industrial transition carries risks in terms of security and privacy issues that arise. In this article, we propose a novel secure network model to enhance network security and employees’ privacy in the edge-enabled industrial IoTs. Experimental results demonstrate encouraging performance rates in terms of accuracy, precision, recall, fall-out, F-measure, and Matthews correlation coefficient against known and unknown bot attacks.
ISSN: 1551-3203
Other Identifiers: 10.1109/TII.2022.3162837
Appears in Collections:Department of Applied Informatics

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