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39 lines
1.5 KiB
39 lines
1.5 KiB
RAPPOR
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======
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RAPPOR is a novel privacy technology that allows inferring statistics about
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populations while preserving the privacy of individual users.
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This repository contains simulation and analysis code in Python and R.
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For a detailed description of the algorithms, see the
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[paper](http://arxiv.org/abs/1407.6981) and links below.
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Feel free to send feedback to
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[rappor-discuss@googlegroups.com][group].
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-------------
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- [RAPPOR Data Flow](http://google.github.io/rappor/doc/data-flow.html)
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Publications
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------------
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- [RAPPOR: Randomized Aggregatable Privacy-Preserving Ordinal Response](http://arxiv.org/abs/1407.6981)
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- [Building a RAPPOR with the Unknown: Privacy-Preserving Learning of Associations and Data Dictionaries](http://arxiv.org/abs/1503.01214)
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Links
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-----
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- [Google Blog Post about RAPPOR](http://googleresearch.blogspot.com/2014/10/learning-statistics-with-privacy-aided.html)
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- [RAPPOR implementation in Chrome](http://www.chromium.org/developers/design-documents/rappor)
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- This is a production quality C++ implementation, but it's somewhat tied to
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Chrome, and doesn't support all privacy parameters (e.g. only a few values
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of p and q). On the other hand, the code in this repo is not yet
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production quality, but supports experimentation with different parameters
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and data sets. Of course, anyone is free to implement RAPPOR independently
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as well.
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- Mailing list: [rappor-discuss@googlegroups.com][group]
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[group]: https://groups.google.com/forum/#!forum/rappor-discuss
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