Third round of Secure and Private IoT Initiative funded projects announced

Daniel Tkacik

Feb 26, 2021


Source: Carnegie Mellon University College of Engineering

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) has announced its third round of funding, which will support 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 were active in working with IoT@CyLab co-directors Anthony Rowe and Vyas Sekar on the request for proposals and proposal review.

“This year we’re continuing a focus on IIoT, but we’re also revisiting some new, relevant, user-facing concerns as they relate to IoT,” Rowe and Sekar shared in a joint statement.

The projects are grouped into three broad research themes: (1) Trustworthy platforms (2) Autonomous healing networks and (3) Accountability. During the execution of these projects, CyLab faculty and students will collaborate with industry sponsors towards the mission of creating the knowledge and capabilities to build secure and privacy-respecting IoT systems. The outcomes from this funding will be presented at the IoT@CyLab annual summit later this year.

Listed below are the funded projects.


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

  • Mayank Goel, assistant professor, Human-Computer Interaction Institute (HCII)


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




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.