At the SEI, we research complex software engineering, cybersecurity, and AI engineering problems; create and test innovative technologies; and transition maturing solutions into practice. We have been ...
Walsh, M., 2024: A Framework for Detection in an Era of Rising Deepfakes. Carnegie Mellon University, Software Engineering Institute's Insights (blog), Accessed ...
Konrad, M., Testa, N., Gates, L., Nolan, C., Shepard, D., Cohen, J., Mellinger, A., Miller, S., and Ludwick, M., 2024: Measuring AI Accuracy with the AI Robustness ...
Schmidt, D., and Robert, J., 2024: Applying Large Language Models to DoD Software Acquisition: An Initial Experiment. Carnegie Mellon University, Software Engineering ...
Executive Order 13587 requires federal agencies that operate or access classified computer networks to implement an insider threat detection and prevention program. Proposed changes to the National ...
Scherlis, B., 2024: Weaknesses and Vulnerabilities in Modern AI: AI Risk, Cyber Risk, and Planning for Test and Evaluation. Carnegie Mellon University, Software ...
Shevchenko, N., 2020: An Introduction to Model-Based Systems Engineering (MBSE). Carnegie Mellon University, Software Engineering Institute's Insights (blog ...
Langston, M., 2017: Six Best Practices for Securing a Robust Domain Name System (DNS) Infrastructure. Carnegie Mellon University, Software Engineering Institute's ...
Spring, J., 2022: Probably Don’t Rely on EPSS Yet. Carnegie Mellon University, Software Engineering Institute's Insights (blog), Accessed November 1, 2025, https ...
Hughes, L., and Jackson, V., 2021: A Framework for DevSecOps Evolution and Achieving Continuous-Integration/Continuous-Delivery (CI/CD) Capabilities. Carnegie Mellon ...
Trzeciak, R., and CERT Insider Threat Center, T., 2017: Announcing the National Insider Threat Center. Carnegie Mellon University, Software Engineering Institute's ...