Scalability Challenges in Privacy-Preserving Federated Learning
Summary
This NIST Cybersecurity Insights article discusses the scalability challenges in privacy-preserving federated learning. It is a collaborative effort between NIST and the UK government’s Responsible Technology Adoption Unit, featuring insights from experts at the University of Liverpool, UK Office of National Statistics (ONS), and the University of Washington Tacoma.
IFF Assessment
The article discusses challenges in privacy-preserving federated learning, allowing defenders to anticipate and mitigate potential risks.
Severity
Defender Context
While not directly a vulnerability, scalability challenges in privacy-preserving federated learning can lead to weaknesses. Defenders should monitor advancements in this field and understand the potential limitations in their own federated learning implementations. Staying abreast of research and best practices is critical to ensuring robust privacy and security.