Date of Award

Spring 1-1-2017

Document Type

Thesis

Degree Name

Master of Science (MS)

First Advisor

Joe McManus

Second Advisor

David Reed

Third Advisor

Levi Perigo

Abstract

The k-anonymity model has become a standard for anonymizing data. However, almost all applications of k-anonymity are used to anonymize large data sets of personally identifiable information owned by a trusted third party before being given to analysists To further research in this this area, this study created a tool called the Anonymity Engine. This tool was built as a web browser plugin that analyzes headers on all web traffic exiting the system and builds a database of relevant quasi-identifier. Users are notified in real time if a data packet would compromise their identity and give the option to not send the data. This tool has also been used to generate data that shows that modifying data before implementing k-anonymity can impact the results. These modified results show that it can make some users more anonymous while reducing the level of privacy for other users depending on the traffic.

Share

COinS