A DDoS Attack Detection System for Industry 5.0 using Digital Twins and Machine Learning
Akshat Gaurav, Brij Bhooshan Gupta, Kwok Tai Chui, Varsha Arya, Elhadj Benkhelifa · 2023
Industry 5.0 is a new paradigm that seeks to improve production via the use of cutting-edge technologies like the Internet of Things (IoT) and cloud computing. Distributed denial of service (DDoS) assaults, for example, may severely harm industrial processes and disrupt the whole supply chain, but this integration of technology also presents significant security issues. Therefore, it is crucial in the age of Industry 5.0 to create reliable DDoS attack detection systems. In this research, we offer a DDoS attack detection system for the Industry 5.0 environment that makes use of Digital Twins (DTs) and Machine Learning (ML). Our method takes use of the strengths of DTs to model the production flow virtually, which can then be used to track the system’s behaviour and spot any hiccups. For further analysis of the DTs’ output data in order to spot possible DDoS assaults, we use explicable ML algorithms like the decision tree classifier.