ML Security Committee

Organisations continue to unlock unprecedented value as they scale their machine learning capabilities across a growing number of use cases. This increasing rate of adoption of machine learning brings along large security challenges across the Data, AI and MLOps tooling and infrastructure.

ML Security is relevant to every phase of the machine learning lifecycle. The diagram below depicts how every stage of the end-to-end machine learning lifecycle is vulnerable to security exploits.

The MLSecOps committee aims to provide an open platform to explore, showcase and discuss challenges and solutions concerning the security of machine learning tooling, systems and use-cases.