End-to-End Security for Evolved Computer Systems
Computer systems are evolving beyond classical notions of desktops/laptops, servers and even smartphones. They are distributed, embedded, capable of learning and can modify our perception of the world. Securing such systems requires an end-to-end perspective. I will demonstrate the utility of this perspective by discussing our 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. Our techniques allow building such automations with least privilege. I will also briefly discuss our efforts at devising threat models for learning-enabled systems that interact with the physical world. One example is a new class of invisible-to-humans physical attack on computer vision.
Earlence Fernandes is an assistant professor of computer science at the University of California, San Diego. 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, research awards from Facebook and Amazon, and the NSF CAREER award. He once hacked a Stop sign, and it is now in a museum.