- Agile
- Artificial Intelligence Engineering
- CERT/CC Vulnerabilities
- Cloud Computing
- Cyber-Physical Systems
- Cybersecurity Center Development
- Cybersecurity Engineering
- Cyber Workforce Development
- DevSecOps
- Edge Computing
- Enterprise Risk and Resilience Management
- Insider Threat
- Model-Based Systems Engineering
- Quantum Computing
- Reverse Engineering for Malware Analysis
- Secure Development
- Situational Awareness
- Software Architecture
- Software Engineering Research and Development
- Technical Debt
The Latest Work from the SEI: Insider Risk, Bias in LLMs, Secure Coding, and Designing Secure Systems
The latest work from SEI technologists in the areas of insider risk, large language models, secure coding and static analysis.
Read More•By Bill Scherlis
In Software Engineering Research and Development
Beyond Capable: Accuracy, Calibration, and Robustness in Large Language Models
For any organization seeking to responsibly harness the potential of large language models, we present a holistic approach to LLM evaluation that goes beyond accuracy.
Read More•By Matthew Walsh, David Schulker, Shing-hon Lau
In Artificial Intelligence Engineering
Cyber-Physical Sensing to Extend the National Intelligence, Surveillance, and Reconnaissance Mesh
With the growing importance of improved sensing for national security, leveraging sensors in consumer products or embedded in devices can be economical, flexible, and timely.
Read More•By Matthew Walsh, David Schulker, Dominic A. Ross, Devin Michael Cortese
In Cyber-Physical Systems
GenAI for Code Review of C++ and Java
Would ChatGPT-3.5 and ChatGPT-4o correctly identify errors in noncompliant code and correctly recognize compliant code as error-free?
Read More•By David Schulker
In Artificial Intelligence Engineering
An Introduction to Hardening Docker Images
Through our work, we have seen stakeholders encountering difficulty with hardening open source container images for vulnerability mitigation.
Read More•By Maxwell Trdina, Sasank Vishnubhatla
In Cybersecurity Engineering
Introduction to MLOps: Bridging Machine Learning and Operations
Machine learning operations (MLOps) has emerged as a critical discipline in artificial intelligence and data science. This post introduces MLOps and its applications.
Read More•By Daniel DeCapria
In Artificial Intelligence Engineering
A Framework for Detection in an Era of Rising Deepfakes
This blog post details the evolving deepfake landscape and introduces a framework for detection.
Read More•By Matthew Walsh
In Cybersecurity Engineering
An Introduction to Model-Based Systems Engineering (MBSE)
Revisit our most popular post of the last four years, which introduces model-based systems engineering, a methodology to support the requirements, design, analysis, verification, and validation associated with the development …
Read More•By Nataliya Shevchenko
In Model-Based Systems Engineering
Challenges to Assuring Large-Scale Systems
National defense efforts have shifted from defeating terrorism to accelerating innovation, with a priority of delivering capability at speed and at scale.
Read More•By Gabriel Moreno, Anton Hristozov, John E. Robert, Mark H. Klein
In Software Engineering Research and Development
Evaluating Static Analysis Alerts with LLMs
LLMs show promising initial results in adjudicating static analysis alerts, offering possibilities for better vulnerability detection. This post discusses initial experiments using GPT-4 to evaluate static analysis alerts.
Read More•By William Klieber, Lori Flynn
In Cybersecurity Engineering
Explore Topics
- Agile
- Artificial Intelligence Engineering
- CERT/CC Vulnerabilities
- Cloud Computing
- Cyber-Physical Systems
- Cybersecurity Center Development
- Cybersecurity Engineering
- Cyber Workforce Development
- DevSecOps
- Edge Computing
- Enterprise Risk and Resilience Management
- Insider Threat
- Model-Based Systems Engineering
- Quantum Computing
- Reverse Engineering for Malware Analysis
- Secure Development
- Situational Awareness
- Software Architecture
- Software Engineering Research and Development
- Technical Debt
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