Please use this identifier to cite or link to this item:
http://arks.princeton.edu/ark:/88435/dsp01db78tf46k| Title: | RAPPOR in Reality |
| Authors: | Jain, Akash |
| Advisors: | Narayanan, Arvind Feamster, Nick |
| Department: | Computer Science |
| Class Year: | 2016 |
| Abstract: | Rappor-js is a practical tool that democratizes access to differential privacy techniques for the bulk collection of data. It harnesses Google’s recent RAPPOR algorithm and is designed to be used by researchers with no background in privacy or programming. By making certain technical decisions on behalf of researchers, a major hurdle to the widespread adoption of differential privacy techniques in real-world settings has been dramatically lowered. This paper justifies the design, parameter and privacy choices made in building rappor-js. It also discusses the circumstances under which this tool can be soundly and reliably used. The final project can be found at http://rapporjs.com. |
| Extent: | 50 pages |
| URI: | http://arks.princeton.edu/ark:/88435/dsp01db78tf46k |
| Type of Material: | Princeton University Senior Theses |
| Language: | en_US |
| Appears in Collections: | Computer Science, 1988-2020 |
Files in This Item:
| File | Size | Format | |
|---|---|---|---|
| Jain_Akash_thesis.pdf | 941.67 kB | Adobe PDF | Request a copy |
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