Accurate and efficient private release of datacubes and contingency tables

  title={Accurate and efficient private release of datacubes and contingency tables},
  author={Graham Cormode and Cecilia M. Procopiuc and Divesh Srivastava and Grigory Yaroslavtsev},
  journal={2013 IEEE 29th International Conference on Data Engineering (ICDE)},
A central problem in releasing aggregate information about sensitive data is to do so accurately while providing a privacy guarantee on the output. Recent work focuses on the class of linear queries, which include basic counting queries, data cubes, and contingency tables. The goal is to maximize the utility of their output, while giving a rigorous privacy guarantee. Most results follow a common template: pick a “strategy” set of linear queries to apply to the data, then use the noisy answers… CONTINUE READING
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