A Secure Network Model Against Bot Attacks in Edge-Enabled Industrial Internet of Things

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.