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Multi-Vector Tracking of WiFi and ZigBee Devices

Location privacy preservation has shifted to the forefront of discussions about next generation wireless networks. While pseudonym-changing schemes have been proposed to preserve an individual's privacy, simulation has shown that new association attack models render these schemes useless. The major contribution of this thesis is the implementation of a tracking network with commodity hardware on the California Polytechnic State University campus which leverages the combination of de-anonymization strategies on captured wireless network data to show the effectiveness of a pseudonym-changing scheme for wireless identification across WiFi and Zigbee protocols.
Date01 June 2019
CreatorsLaverty, Calvin Andrew
Source SetsCalifornia Polytechnic State University
Detected LanguageEnglish
SourceMaster's Theses

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