We present a graphical framework containing certain in nite pro les of probability
distributions that result from an attack on an anonymity system. We represent currently
popular anonymity metrics within our framework to show that existing metrics base their
decisions on just some small piece of information contained in a distribution. This explains
the counterintuitive, thus unsatisfactory, anonymity evaluation performed by any of these
metrics for carefully constructed examples in literature. We then propose a new anonymity
metric that takes entire pro les into consideration in arriving at the degree of anonymity
associated with a probability distribution. The comprehensive approach of our metric results
in correct measurement. A detailed comparison of our new metric, especially with the
popular metrics based on Shannon entropy, gives the rationale and degree of disagreement
between these approaches.
vi / Thesis (M.S.)--Wichita State University, College of Engineering, Dept. of Electrical Engineering and Computer Science
| Identifer | oai:union.ndltd.org:WICHITA/oai:soar.wichita.edu:10057/5043 |
| Date | 07 1900 |
| Creators | Jiang, Nan |
| Contributors | Bagai, Rajiv |
| Publisher | Wichita State University |
| Source Sets | Wichita State University |
| Language | en_US |
| Detected Language | English |
| Type | Thesis |
| Format | ix, 41 p. |
| Rights | © Copyright 2011 by Nan Jiang. All rights reserved |
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