Stanford Security Lunch

Abstract: Type 1 Diabetes is a metabolic disorder where an individual's pancreas stops producing insulin. To compensate, they inject synthetic insulin. Computer systems, called automated insulin delivery systems, exist that inject insulin automatically. However, insulin is a dangerous hormone, where too much insulin can kill people in a matter of hours and too little insulin can kill people in a matter of days. Because of this risk, no current automated insulin delivery systems use ML to calculate insulin doses, despite the overwhelming evidence from the literature that deep neural networks are a perfect fit for the problem. In this talk, we take on the challenge of building a new ML-based automated insulin delivery system, called GlucOS. Our innovation is in the security and safety mechanisms we use to enable ML to control an insulin pump safely. One interesting finding is that humans are a key component to providing strong security, and our work includes them first class from the start.

Bio: Sam King is a professor in the CS department at UC Davis. He has worked on security for web browsers and hardware, and more recently on applying security principles to stop financial fraud. Currently, his research focus is on building trustworthy computer systems for people living with disabilities. Throughout his career, Sam has focused on using novel research to solve real-world problems. Among the highlights are that the security architecture of Google Chrome and Mozilla Firefox are based on his research, and software that came out of his lab to stop credit card fraud ran on more than 1 billion devices, stopping an estimated $100M in fraud losses and introducing ethics and equity to fraud prevention.