Daniel Cebul was a Semester Research Analyst at Georgetown’s Center for Security and Emerging Technology (CSET), where he worked on the CyberAI Project. His research interests focus broadly on autonomous weapon systems, strategic stability and the offense-defense balance. Previously, Daniel was an editorial fellow at Defense News and C4ISRNET. He has also authored research on air and missile defense systems and autonomous weapon systems at the Center for Strategic and International Studies. Daniel is a Georgetown Security Studies master’s student with a concentration in Technology & Security. He holds a B.A. in Political Science (cum laude) from Kenyon College.
Destructive Cyber Operations and Machine LearningNovember 2020
Machine learning may provide cyber attackers with the means to execute more effective and more destructive attacks against industrial control systems. As new ML tools are developed, CSET discusses the ways in which attackers may deploy these tools and the most effective avenues for industrial system defenders to respond.