Date of Award

3-24-2016

Document Type

Thesis

Degree Name

Master of Science

Department

Department of Electrical and Computer Engineering

First Advisor

Benjamin W. Ramsey, PhD.

Abstract

Wireless Sensor Networks (WSN) are a growing subset of the emerging Internet of Things (IoT). WSNs reduce the cost of deployment over wired alternatives; consequently, use is increasing in home automation, critical infrastructure, smart metering, and security solutions. Few published works evaluate the security of proprietary WSN protocols due to the lack of low-cost and effective research tools. One such protocol is ITU-T G.9959-based Z-Wave, which maintains wide acceptance within the IoT market. This research utilizes an open source toolset, presented herein, called EZ-Wave to identify methods for exploiting Z-Wave devices and networks using Software-Defined Radios (SDR). Herein, techniques enabling active network reconnaissance, including network enumeration and device interrogation, are presented. Furthermore, a fuzzing framework is presented and utilized to identify three packet malformations resulting in anomalous device behavior. Finally, a method for classifying the three most common Z-Wave transceivers with >99% accuracy using preamble manipulation is identified and tested.

AFIT Designator

AFIT-ENG-MS-16-M-020

DTIC Accession Number

Pending

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