Logos from the companies who supported the 2021 projects

Source: CyLab

Funding for these IoT@CyLab projects was made possible by sponsorships from Amazon Web Services, AT&T Business, Cisco, Infineon Technologies, and Nokia Bell Labs.

Carnegie Mellon CyLab’s Secure and Private IoT Initiative (IoT@CyLab) is supporting 12 Internet of Things (IoT)-related projects for one year. While all IoT security and privacy topics are within scope and the focus on Industrial IoT (IIoT) is still central, IoT@CyLab is adding an emphasis on research to help people stay secure as they bring more connected devices into the home as many people continue work from home during the COVID-19 pandemic.

Funding for these projects was made possible by sponsorships from Amazon Web Services, AT&T Business, Cisco, Infineon Technologies, and Nokia Bell Labs. These sponsors actively worked with IoT@CyLab co-directors Anthony Rowe and Vyas Sekar on the request for proposals and proposal review. 

The projects are grouped into three broad research themes:

Funding for these projects was made possible by sponsorships from Amazon Web Services, AT&T Mobility, Cisco, Infineon Technologies, and Nokia Bell Labs. These sponsors were active in working with IoT@CyLab co-directors Anthony Rowe and Vyas Sekar on the request for proposals and proposal review.

Not all IoT-related projects at CMU are funded under this initiative. Explore other IoT projects at CMU.

 

Trustworthy platforms

Distributed Data Structures for Federated Learning

  • Heather Miller, assistant professor, Institute for Software Research (ISR)

Enabling Privacy-Preserving IoT Apps and Data Analytics

Teaching Old Sensors New Tricks to Enable Plug-and-Play Activity Recognition for Opportunistic Health Sensing

 

Autonomous healing networks

Systematic Attack Recovery in Industrial Control Systems

Secure, Resilient, and Continuous Machine Learning in Edge Networks

  • Osman Yagan, associate research professor, Electrical and Computer Engineering (ECE)
  • Soummya Kar, professor, ECE

Autonomous Cyber Defense for IIoT using Deductive-Reasoning and Reinforcement Learning

Oblivious Network Security Analysis using Generative Adversarial Networks

 

Accountability

Third-Party Network Traffic Attribution for IoT, TV, Web, and Mobile

Making smart homes safe for incidental users

Robust and explainable ML-based anomaly detection for industrial IoT

Wireless Anomaly Detection in Industrial IoT

Assuring safety and resilience in affordable IoT systems

 

For information on how your company can get involved in IoT@CyLab or other security and privacy research at CMU, contact a member of the CyLab partnerships team.