SPQR Poster Session

Throughout the summer of 2020, we had ten Undergraduate Interns who worked on various projects. This session is for them to present their work.

View their posters

SPQR Lab Manifesto

We at the SPQR lab assert that Black lives matter. We stand with the Black community, including all those who are Black, African American, or members of the larger African Diaspora. We categorically reject racism, hate, violence, and inequity and harassment in any form. The SPQR Lab is committed to provide a safe and equitable environment, to create and maintain a culture of support and inclusion, and to celebrate and use our differences to improve Science. #blacklivesmatter.

The SPQR Lab Team

About the SPQR Group

The SPQR Group at the University of Michigan works broadly on research problems pertaining to embedded security. We explore the research frontiers of computer science, electrical and computer engineering, and healthcare. Our latest projects examine how to protect analog sensors from intentional electromagnetic, acoustic interference, and light injection.

Recent Projects

(View more in our Project page )
Oven photo for N95 Masks

Verifiable Decontamination of N95 Masks

It's extremely important for the global health to ensure that front-line healthcare workers have access to a supply of N95 masks while caring for COVID-19 patients. A global shortage of N95 respirator masks has led to the emergency construction of various decontamination systems for reuse of disposable masks worn by healthcare workers. Any decontamination must protect against damage to the masks' filter performance...

SOK Figure

SoK: Formalizing Analog Sensor Security

Over the last six years, several papers demonstrated how intentional analog interference based on acoustics, RF, lasers, and other physical modalities could induce faults, influence, or even control the output of sensors. Damage to the availability and integrity of sensor output carries significant risks to safety-critical systems that make automated decisions based on trusted sensor measurement. Established signal processing models use transfer functions to express...

Light Commands Figure

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.

Good Reads

Related Initiatives

SPQR Blog Posts (view all blogs)