Our ML Security Lab focuses on protecting machine learning models from current threats and future attacks, using both adversarial techniques and resilience frameworks. We research, test, and develop the latest security tools to keep your ML models secure and resilient during design, development, testing and production.

Machine Learning will greatly enhance your business, but it's also becoming increasingly targeted. Our lab ensures that as your AI evolves, its security scales with it — protecting intellectual property, sensitive data, and critical decision systems.

We defend machine learning systems against a wide range of emerging threats — including model inversion, model theft, adversarial examples, and data poisoning. Our lab ensures your models remain private, tamper-resistant, and trustworthy by applying robust security controls across training, inference, and deployment.