Preserving Privacy While Sharing Data
Traditional approaches to safeguarding privacy when sharing data can fail, exposing organizations to litigation and regulatory penalties. Differential privacy gives organizations a way to manage the trade-off between privacy and data accuracy, and to release statistics or create new data sets while controlling the degree to which privacy can be compromised. The authors describe the challenges and potential benefits of using this mathematical approach to protecting data privacy.