June 5, 10:15am
Location: Magnolia

The Role of AI in Industrial IoT Cybersecurity

In this talk we discuss the role that AI plays in cybersecurity of industrial IoT. As the integration of IoT in industrial systems proliferates, it is imperative to also consider the potential vulnerabilities that are being created by these technologies. Hackers have already famously used SCADA and PLC systems to sabotage industrial facilities. As such, it is important to understand the exposure to malfeasance to ensure that industrial IoT does not end up being the enabling mechanism for unauthorized access to the system. AI plays a dual role in this arena: For one, it can be used to protect form attacks through Anomaly detection of unusual patterns of network activity; gathering and analyzing data to provide real-time information about potential threats to IoT systems; Vulnerability assessment by scanning IoT systems for known vulnerabilities; blocking malicious traffic in real-time; and  enhancing authentication processes by using biometric data. On the flip side, AI is actually being used to attack industrial IoT  through malware that can bypass traditional security systems and infect IoT devices; AI-powered network attacks; and AI-powered reconnaissance that gathers information about IoT systems. It is important to understand both roles to ensure that operations are not interrupted. A specific focus of this talk is on systems that are used for Predictive Maintenance (or PHM) as it heavily taps into the use of SCADA, PLC, and other systems that are part of an attack surface in industrial plants.

Kai Goebel is VP and lab director of the Intelligent Systems Lab at Palo Alto Research Center (PARC). He is also an Adjunct Professor at Lulea Technical University in the Operations and Maintenance Department. His particular interest is systems health management, decision-making, and autonomy for a broad spectrum of cyber-physical systems in manufacturing, transportation, energy, aerospace, and defense sectors. Prior to joining PARC, Dr. Goebel worked at NASA Ames Research Center where he was the Area Lead for Discovery and Systems Health, There he founded the Prognostics Center of Excellence which spearheaded development of prognostic techniques, metrics, and generation of publicly available run-to-failure datasets for various components. Earlier, he was a senior research scientist at General Electric Corporate Research & Development center between 1997 and 2006. He has fielded numerous applications for aircraft engines, transportation systems, energy applications, medical systems, and manufacturing systems. He holds 19 patents and has published around 400 papers. He received his Ph.D. in Mechanical Engineering from UC Berkeley in 1990. He is a member of IEEE, AAAI, ASME, and SAE; co-founder of the Prognostics and Health Management Society; and associate editor of the International Journal of PHM.