As facial recognition, surveillance and smart vehicles become an accepted part of our daily lives, product and chip designers are coming to grips with the business need to secure the data that passes through their systems. Training data, the resulting model data and how decisions are made and acted on can be proprietary information for the product, and important to keep out of competitors’ hands. Inputs from sensors and cameras can contain legally protected data, and the data may create ethical and privacy concerns as cameras and microphones in homes, cars and public settings explode in number. This presentation will describe typical security concerns in vision systems today, including potential weaknesses in training-to-inferencing systems where data can be compromised, and discuss different approaches to security.