Managing Vulnerabilities in Machine Learning and Artificial Intelligence Systems
The current paradigm of vulnerability management might have to adapt to include machine learning (ML) and artificial intelligence (AI) systems. In this SEI Podcast, Allen Householder, Jonathan Spring, and Nathan VanHoudnos discuss how to manage vulnerabilities in AI/ML systems.
About the Speaker
Jonathan Spring is an SEI alumni employee.
Jonathan Spring is a senior member of the technical staff with the CERT division of the Software Engineering Institute (SEI) at Carnegie Mellon University. Spring began working at the SEI in 2009. Prior posts include adjunct professor at the University of Pittsburgh’s School …Read more
Allen D. Householder is a senior vulnerability researcher in the CERT Division of Carnegie Mellon University's Software Engineering Institute. Householder's research interests include applications of complex systems theory and machine learning to software and system security, fuzzing, and modeling of information sharing and trust among cybersecurity responders.