The study explores the risks and tradeoffs when adapting enterprise-IT security and zero trust principles to weapon systems.

Ruefle, R., 2017: Critical Asset Identification (Part 1 of 20: CERT Best Practices to Mitigate Insider Threats Series). Carnegie Mellon University, Software ...

Robert, J., and Schmidt, D., 2024: 10 Benefits and 10 Challenges of Applying Large Language Models to DoD Software Acquisition. Carnegie Mellon University, Software ...

DeCapria, D., 2025: DataOps: Towards More Reliable Machine Learning Systems. Carnegie Mellon University, Software Engineering Institute's Insights (blog), Accessed ...

The Software Engineering Institute is a leader in researching complex solutions, connecting AI, cyber, and software strategies for maximum impact. Since 1984, the SEI has been one of only 10 Federally ...

The SEI is participating at the SciTech Forum 2026 ...

MOBSTA is a robustness testing tool for ROS that tests autonomous systems under realistic but rare conditions that are not represented in training data and difficult to replicate during field testing.

The October 23 virtual workshop will feature presentations on dataset generation, exploration, preparation, and testing for ensuring data quality when training AI systems.

At the November event, co-organized by the SEI, artificial intelligence experts will present case studies and research and development in building AI systems for safety-critical applications.

For the Department of Defense (DoD) to safely and quickly adopt new software capabilities, especially autonomous systems, we must improve every step in the development and engineering process to ...