Thesis Defense Announcement for Logan Smith — 03/09/2021 at 1:00 PM

March 3, 2021

Faculty and Students,

You are cordially invited to my thesis defense:

Candidate: Logan Smith

Degree: M.S. Electrical & Computer Engineering

Dissertation Title: Machine Learning for Wireless Signal Learning

Date and time: Tuesday, March 9th, 1-2pm

Venue: Webex at


Dr. John E. Ball
(Major Professor)

Dr. Bo Tang
(Committee Member)

Dr. Maxwell Young
(Committee Member)

Dr. James E. Fowler
(Committee Member)


Wireless networks are vulnerable to adversarial devices by spoofing the digital identity of valid wireless devices, allowing unauthorized devices access to the network. Instead of validating devices based on their digital identity, it is possible to use their unique ”physical fingerprint” caused by changes in the signal due to deviations in wireless hardware. In this thesis, the physical fingerprint is validated by performing classification with complex-valued neural networks (NN), achieving a high level of accuracy in the process. Additionally, zero-shot learning (ZSL) is implemented to learn discriminant features to separate legitimate from unauthorized devices using outlier detection and then further separate every unauthorized device into their own cluster. Our approach allows 42% of unauthorized devices to be identified as unauthorized and correctly clustered

Best Regards,

Logan Smith