Loading Events

« All Events

  • This event has passed.

IoT Device Analysis based on the Manufacturer Usage Description (MUD) Protocol

Sep 19, 2018 @ 12:00 pm - 1:30 pm

IoT Device Analysis based on the Manufacturer Usage Description (MUD) Protocol


Dr. Mihail Sichitiu


IoT devices are expected to increase in number exponentially in the next years. Many different manufacturers will produce a vast number of different models, all including custom software of highly variable quality and security. Especially the security is often overlooked when manufacturers have to deliver functionality on a tight schedule.

In this talk we focus on an approach we developed involving capturing and demodulating wireless packets from IoT devices, and analyzing the resulting packet trace for usage patterns. These patterns can then be described and enforced using the Manufacturer Description Protocol (MUD): originally MUD was developed to restrict the degrees of freedom that an IoT device (or any network connected device) has (e.g., limit the range of ports used). In this project we use it to further characterize (limit) the normal behavior of an IoT device, and thus allowing for detecting (and preventing) abnormal behavior.


WEB/CONFERENCE CALL INFO: We are going to use the NC State WebEx for the web conference. Please note that this WebEx belongs to NC State and can not be downloaded directly from Cisco. Also, it should work on iPhones and iPads via the WebExApp. A good internet connection is recommended. For better audio, please join via computer and then have the meeting call your number or call in directly using one of the numbers below. When not speaking, please mute your phone to avoid background noise. When it’s time, join the WebEx meeting from here:



919-513-9329 (WolfMeeting)

Access Code: 996 474 981



Sep 19, 2018
12:00 pm - 1:30 pm


Partners I, 1017 Main Campus Dr, Raleigh, NC 27606, USA
800 Main Campus Dr United States



Connect With Us

LAS aims to bring together a multi-disciplinary group of academic, industry, and government researchers, analysts and managers together to re-engineer the intelligence analysis process to promote predictive analysis. LAS will do this by conducting both classified and unclassified research in a variety of areas of research. The research done in this area will serve as the foundation for mission effects and integrated back into the enterprise.

If you would like to sign up for our email distribution list, please fill out this form: