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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
Extent: 50 pages
Type of Material: Princeton University Senior Theses
Language: en_US
Appears in Collections:Computer Science, 1988-2017

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