Date of Award

9-2021

Document Type

Thesis

Degree Name

Master of Science in Computer Science

Department

Department of Electrical and Computer Engineering

First Advisor

Barry E. Mullins, PhD

Abstract

The risk of information leakage in 802.11ac allows an eavesdropper to monitor wireless traffic and correlate physical locations between devices, as well as environment changes such as the motion of a person. Previous pattern-analysis mitigation methods, which used nonexistent devices to fool an eavesdropper, are not effective in an 802.11ac network, because devices on the network can be correlated to their physical location, which a nonexistent device does not have. Further, additional information about motion in the target environment can be observed and analyzed, providing a new potential for pattern analysis and sensing. 802.11ac makes it possible to plug in a wireless adapter in monitor mode, listen, and analyze, without specialized equipment. The present work provides tools and methods for basic analysis of802.11ac beamforming feedback, demonstrates their utility and limitations, discusses the qualitative aspects of the analysis, suggests avenues of future development to refine and improve such analysis, and discusses the applications of the existing analysis.

AFIT Designator

AFIT-ENG-MS-21-S-018

DTIC Accession Number

AD1149661

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