Abstract

The integration of the Internet of Things (IoT) into smart critical infrastructure has significantly enhanced monitoring, control, and efficiency. However, this integration introduces new cybersecurity risks, as IoT devices can become vulnerable points for attackers targeting essential services such as electricity, water, and transportation. Addressing these risks requires robust intrusion detection systems to monitor and mitigate potential cyber threats. This talk explores the application of deep learning and federated learning techniques to enhance intrusion detection in IoT-enabled smart critical infrastructure. It will also cover the challenges and security implications of using Artificial Intelligence (AI) in the cybersecurity of smart critical infrastructure and discuss current solutions to ensure AI systems remain safe, secure, and resilient against cyber-attacks.

Zoom link: https://cam-ac-uk.zoom.us/j/82810963958?pwd=ukzuxkUpQRIPDaekbPb706z6ZUPn0E.1