Private AI Collaborative Research Institute

The Private AI Collaborative Research Institute will focus its efforts on overcoming five main challenges:

•   Training data is decentralized in isolated silos and often inaccessible.
•   Today’s solutions are insecure and require a single trusted data center.
•   Centralized models become obsolete quickly.
•   Centralized compute resources are costly and throttled by communication and latency.
•   Federated machine learning (FL) is limited.
   

While FL can access data at the edge, it cannot reliably guarantee privacy and security. Here is where Prof. Dr. Dmitrienko, head of the research group Secure Software Systems at the University of Würzburg, will contribute towards designing a framework for Federated Learning (FL) resilient against security and privacy threats. The design will incorporate security mechanisms against various attack vectors such as data poisoning and model inference. It will focus on integration of hardware-assisted security and trusted execution environments of varying capabilities for achieving improved privacy and integrity guarantees. 

More information at private-ai.org

People involved: Prof. A. Dmitrienko, Christoph Sendner, and Torsten Krauß.