Yan Michalevsky: 2015 Security Workshop

Modern mobile platforms like Android enable ap- plications to read aggregate power usage on the phone. This information is considered harmless and reading it requires no user permission or notification. We show that by simply reading the phone’s aggregate power consumption over a period of a few minutes an application can learn information about the user’s location. Aggregate phone power consumption data is extremely noisy due to the multitude of components and applications simultaneously consuming power. Nevertheless, we show that by using machine learning techniques, the phone’s location can be inferred. We discuss several ways in which this privacy leak can be remedied.

Yan Michalevsky is a PhD student at Stanford University, advised by Dan Boneh. He recently focused on mobile security and privacy. His works on side-channel attacks on mobile devices were presented at Usenix and BlackHat security conferences. Previously, he held several positions in industry as a team manager, independent contractor, and software architect and developer, mostly in the fields of networks, embedded software and security. He holds a BSc in Electrical Engineering from the Technion, and an MS in Electrical Engineering from Stanford University.