Geographic Partitioning Techniques for the Anonymization of Health Care Data

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Creator: 

Croft, William Lee

Date: 

2015

Abstract: 

As the demand for the availability of detailed health care data sets continues to increase, organizations are faced with the conflicting interests of releasing this important information while protecting the confidentiality of the individuals to whom the data pertains. A major concern when releasing health care data is the geographic information which has a large influence on the re-identifiability of the data and yet is essential for many research applications. In this work, a novel system for data anonymization is presented. At the core of the system is the aggregation of an initial regionalization guided by the use of a Voronoi diagram. Testing is conducted via an implementation designed to run and analyze the results of the various combinations of approaches. In addition, a comparative test is conducted with another system, GeoLeader. It is shown that our system is capable of producing comparable results with a much faster running time.

Subject: 

Computer Science

Language: 

English

Publisher: 

Carleton University

Thesis Degree Name: 

Master of Computer Science: 
M.C.S.

Thesis Degree Level: 

Master's

Thesis Degree Discipline: 

Computer Science

Parent Collection: 

Theses and Dissertations

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