Network Visualization of IoT devices

Project Summary

A team of students, in conjunction with Duke’s Office of Information Technology, will use of Duke’s network traffic data to perform IoT device behavioral fingerprinting that can be employed to identify device types. The data will be used to analyze trends and risks, develop security best practices, and build machine learning models that can be used to detect similar device types. Students will work directly with the network data and have access to the analytics tools used in OIT and will have a great opportunity for exploration of the data in consultation with OIT network, security and data analytics professionals.

Project Lead: Will Brockselsby

Themes and Categories
Interdisciplinary Inquiry
Data+
Year
2019
Contact
Paul Bendich
Mathematics
bendich@math.duke.edu

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