src.private_count_mean

This subpackage contains implementations of algorithms for calculating private count means using the Count-Mean-Sketch (CMS) approach. The Count-Mean-Sketch is a probabilistic data structure that allows for efficient frequency estimation while providing differential privacy guarantees. This subpackage includes both client-side and server-side implementations for privacy-preserving data aggregation.

Modules:

  • cms_client_mean.py: Implements the client-side logic for generating private count means.
  • private_cms_client.py: Contains the client-side logic for perturbing data before sending it to the server.
  • private_cms_server.py: Implements the server-side logic for aggregating and analyzing perturbed data.

Main Functions:

  • execute_client: Simulates the client side of the privatized Count-Min Sketch for all elements in the dataset.
  • server_simulator: Simulates the server side of the privatized Count-Min Sketch, processes the privatized data, and estimates frequencies.
  • update_sketch_matrix: Updates the sketch matrix based on the privatized data received from the client.
  • estimate_client: Estimates the frequency of an element based on the private CMS sketch matrix.
 1"""
 2This subpackage contains implementations of algorithms for calculating private count means
 3using the Count-Mean-Sketch (CMS) approach. The Count-Mean-Sketch is a probabilistic data
 4structure that allows for efficient frequency estimation while providing differential privacy
 5guarantees. This subpackage includes both client-side and server-side implementations for
 6privacy-preserving data aggregation.
 7
 8Modules:
 9- cms_client_mean.py: Implements the client-side logic for generating private count means.
10- private_cms_client.py: Contains the client-side logic for perturbing data before sending it to the server.
11- private_cms_server.py: Implements the server-side logic for aggregating and analyzing perturbed data.
12
13Main Functions:
14- execute_client: Simulates the client side of the privatized Count-Min Sketch for all elements in the dataset.
15- server_simulator: Simulates the server side of the privatized Count-Min Sketch, processes the privatized data, and estimates frequencies.
16- update_sketch_matrix: Updates the sketch matrix based on the privatized data received from the client.
17- estimate_client: Estimates the frequency of an element based on the private CMS sketch matrix.
18"""