Grant: Canada Research Chairs

The fitness tracker on your wrist or the digital camera on your desk are examples of embedded devices, which are single-purpose devices used commonly throughout the world. With the growing use of Artificial Intelligence (AI) systems in cyber security, we expect new threats towards embedded devices that are more challenging to detect, prevent and attribute. Most organizations and governments that currently deploy embedded devices are ill-equipped to assess or address the potential security problems, however there are several benefits to predicting and mitigating potential risks. As Canada Research Chair in Security and Privacy, Natalia Stakhanova plans to discover weak points in the deployed devices at a large scale. This approach will offer unprecedented benefits that will harden systems, bolster defenses, and limit the overall attack surfaces. The uniqueness of the research is its ability to indicate where hostile actions will be taking place and mitigate them before they occur giving companies critical time to address the problems without incurring the damages. Stakhanova’s research aims to offer fundamental methodological support for predictive analytics in next-generation embedded devices and give researchers and security practitioners automated and robust tools to predict, assess, and mitigate these threats.