Opportunities
There are several research opportunities for students to join the SPQR Lab at Michigan! The opportunities range from cyber-physical security research to medical device security. We are interested in working with students who share a commitment to our values.We are especially looking for people with interest and excitement in any of the following areas:
- Embedded Systems
- Signal Processing
- Computer Vision
- Medical Devices
- Physical Modeling and Simulation
- Machine Learning
Ph.D. and Masters Students
The link to apply for graduate school is here:Undergraduates
We have mentored many successful undergraduate researchers in the past. We tend to recruit new students at the beginning of each semester. If you are interested in the working in our lab contact us at spqr-team@umich.edu a few weeks before the beginning of a new semester. Please do browse our recent research papers as preparation.Recent Projects
Light Commands
Light Commands is a vulnerability of MEMS microphones that allows attackers to remotely inject inaudible and invisible commands into voice assistants, such as Google assistant, Amazon Alexa, Facebook Portal, and Apple Siri using light. In our paper we demonstrate this effect, successfully using light to inject malicious commands into several voice controlled devices such as smart speakers, tablets, and phones across large distances and through glass windows.
Side Eye: Extract Sound from Muted Videos
Side Eye is a technique that allows adversaries to extract acoustic information from a stream of camera photos. When sound energy vibrates the smartphone body, it shakes camera lenses and creates tiny Point-of-View (POV) variations in the camera images. Adversaries can thus infer the sound information by analyzing the image POV variations. Side Eye enables a family of sensor-based side channel attacks targeting acoustic eavesdropping even when smartphone microphone is disabled.
Poltergeist: Manipulating Computer Vision Systems with Acoustics and Motion
As cameras become increasingly pervasive, the security and privacy of computer vision systems is a focus of SPQR's research. Our work explores how different physical processes such as acoustics and motion are captured and interpreted by cameras, and how malicious parties may exploit these effects to intentionally adulterate vision systems’ output or exfiltrate sensitive information from it. Our recent research shows acoustic injections into cameras may cause accidents to autonomous vehicles.