Computer systems have evolved beyond classical notions of personal computers, servers and even smartphones. They are distributed, embedded, capable of learning and can modify our perception of the physical world. Securing such systems requires an end-to-end perspective. I will demonstrate the utility of this perspective by discussing my recent results on: (1) building least-privilege distributed systems with applications to the Internet of Things; and (2) establishing threat models for systems that learn. Specifically, I will focus on the class of low-code systems that allow end-users to create small automations that connect their digital and physical resources. My techniques allow building such automations with least privilege. I will also briefly discuss my efforts at devising threat models for learning-enabled systems that interact with the physical world.
Earlence Fernandes is an assistant professor of computer science at the University of Wisconsin-Madison. His goal is to enable society to gain the benefits of evolved computer systems without the security and privacy risks. Earlence is a recipient of multiple best paper awards, a Facebook research award and the NSF CAREER award. He once hacked a Stop sign, and it is now in a museum.