• Corpus ID: 215768661

Unifying Privacy Loss Composition for Data Analytics

  title={Unifying Privacy Loss Composition for Data Analytics},
  author={Mark Cesar and Ryan M. Rogers},
Differential privacy (DP) provides rigorous privacy guarantees on individual's data while also allowing for accurate statistics to be conducted on the overall, sensitive dataset. To design a private system, first private algorithms must be designed that can quantify the privacy loss of each outcome that is released. However, private algorithms that inject noise into the computation are not sufficient to ensure individuals' data is protected due to many noisy results ultimately concentrating to… 
1 Citations
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