- Agile
- Artificial Intelligence Engineering
- CERT/CC Vulnerabilities
- Cloud Computing
- Cyber-Physical Systems
- 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
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.
• By William Klieber, Lori Flynn
In Cybersecurity Engineering
Measuring AI Accuracy with the AI Robustness (AIR) Tool
Understanding your artificial intelligence (AI) system’s predictions can be challenging. In this post, SEI researchers discuss a new tool to help improve AI classifier performance.
• By Michael D. Konrad, Nicholas Testa, Linda Parker Gates, Crisanne Nolan, David James Shepard, Julie B. Cohen, Andrew O. Mellinger, Suzanne Miller, Melissa Ludwick
In Artificial Intelligence Engineering
A Roadmap for Incorporating Positive Deterrence in Insider Risk Management
Positive deterrence reduces insider risk through workforce practices that promote the mutual interests of employees and their organization.
• By Andrew P. Moore
In Insider Threat
The Latest Work from the SEI: Counter AI, Coordinated Vulnerability Disclosure, and Artificial Intelligence Engineering
This post highlights the latest work from the SEI in artificial intelligence engineering, coordinated vulnerability disclosure for machine learning, and counter AI.
• By Bill Scherlis
In Software Engineering Research and Development
Generative AI and Software Engineering Education
Educators have had to adapt to rapid developments in generative AI to provide a realistic perspective to their students. In this post, experts discuss generative AI and software engineering education.
• By Ipek Ozkaya, Douglas Schmidt (Vanderbilt University)
In Artificial Intelligence Engineering
Acquisition Archetypes Seen in the Wild, DevSecOps Edition: Cross-Program Dependencies
Shared capabilities can help manage costs and complexities but can also result in cross-program dependencies. This post examines this phenomenon in a DevSecOps context.
• By William E. Novak
In DevSecOps
3 Recommendations for Machine Unlearning Evaluation Challenges
Machine unlearning (MU) aims to develop methods to remove data points efficiently and effectively from a model without the need for extensive retraining. This post details our work to address …
• By Keltin Grimes, Collin Abidi, Cole Frank, Shannon Gallagher
In Artificial Intelligence Engineering
Building Quality Software: 4 Engineering-Centric Techniques
Why is it easier to verify the function of a software program rather than its qualities? This post outlines 4 engineering-centric techniques to creating quality software.
• By Alejandro Gomez
In Software Architecture
Weaknesses and Vulnerabilities in Modern AI: AI Risk, Cyber Risk, and Planning for Test and Evaluation
Modern AI systems pose consequential, poorly understood risks. This blog post explores strategies for framing test and evaluation practices based on a holistic approach to AI risk.
• By Bill Scherlis
In Artificial Intelligence Engineering
Weaknesses and Vulnerabilities in Modern AI: Integrity, Confidentiality, and Governance
In the rush to develop AI, it is easy to overlook factors that increase risk. This post explores AI risk through the lens of confidentiality, governance, and integrity.
• By Bill Scherlis
In Artificial Intelligence Engineering
Explore Topics
- Agile
- Artificial Intelligence Engineering
- CERT/CC Vulnerabilities
- Cloud Computing
- Cyber-Physical Systems
- 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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