Our mission is to tackle current and upcoming challenges in machine-learning-based automated systems, privacy, and security, including scalability issues, IP protection and adversarial machine learning.
As malicious users have increasing incentives to trick machine learning algorithms, we develop new defenses throughout all layers: algorithm design, software, and underlying hardware. Moreover, as popularity in AI spikes and competition rapidly grows, IP protection for pre-trained machine learning models is of unprecedented importance. The rise of embedded and IoT (Internet of Things) devices poses an additional challenge to the development of lightweight secure systems powered by machine learning.
For more information, please visit the CYSMICS homepage