Advancing Industrial Internet of Things cybersecurity with Artificial Intelligence

The University's research, titled'A Multi-Layer Deep Learning Approach for Malware Classification in 5G-Enabled IIoT,' details the cutting-edge AI- and deep learning-based malware detection system that looks to safeguard the Industrial Internet of Things from cyber-attacks. In recent years, the Industrial Internet of Things has gained traction because of its ability to create novel communication networks between different aspects of industry and power the evolution to Industry 4.0. The Industrial Internet of Things is powered by wireless 5G connectivity, and AI is able to examine and resolve critical problems that enhance the operational performance of industries, such as manufacturing and healthcare. Whereas the Internet of Things is user-centric, connecting televisions, voice assistants, and refrigerators, for example, the Industrial Internet of Things optimises the health, safety, and efficiency of larger systems, connecting hardware with software and performing data analysis to provide insights in real-time. Despite the various benefits of the Industrial Internet of Things, it also carries a range of vulnerabilities, including security threats such as attacks that disturb the network or drain resources.