Skip to content

Latest commit

 

History

History
20 lines (14 loc) · 653 Bytes

README.md

File metadata and controls

20 lines (14 loc) · 653 Bytes

PyPrivacy: Python Privacy framework

A wrapper for Machine Learning and Data Science libraries that allows to control and enforce data usage policies. Released data can be misused, but releasing data access is crucial for the functionality of many services.

Main idea

Our framework binds datasets or even individual data points with the corresponding policies which specify how the developer can use them.

Project plan

  1. Integration with Jupyter notebook
  2. Release beta version
  3. Use cases implementation
  4. (Potentially) Implement SMC and homomorphic encryption

If you are interested in learning more, email: eugene@cs.cornell.edu