Artificial Intelligence-Powered Security and Resilience for Cyber-Physical Systems

As Internet of Things systems become widely adopted, cyber-physical systems offer smarter environments and services than earlier networked systems by leveraging and integrating sensed data from various types of sensors. Despite adopting the benefits of the IoT technologies, cyber-physical systems have various weaknesses due to existing vulnerabilities in wireless networks. With massively connected nodes that push sensed data, the cyber threat surface leaves more nodes as target points to enter the monitoring network. This lecture will consist of the following parts: 1) A brief introduction to the vulnerabilities and countermeasures in IoT and IIoT cybersecurity with a focus on threat models and attacks surfaces in cyber-physical critical infrastructures, 2) State of the art in machine learning-based intrusion detection in IoT and cyber-physical systems in the network layer, 3) The interplay between artificial intelligence and system/application-level security issues in cyber-physical settings, 3) Open issues, challenges and future directions in this field are going to be presented for the researchers interested in this field.