This work is at the intersection of two lines of research. One line, initiated by Dinur and Nissim, investigates the price, in accuracy, of protecting privacy in a statistical dat...
A mechanism for releasing information about a statistical database with sensitive data must resolve a trade-off between utility and privacy. Publishing fully accurate information ...
Arpita Ghosh, Tim Roughgarden, Mukund Sundararajan
Most previous research on privacy-preserving data publishing, based on the k-anonymity model, has followed the simplistic approach of homogeneously giving the same generalized val...
Wai Kit Wong, Nikos Mamoulis, David Wai-Lok Cheung
In this paper, we propose the first formal privacy analysis of a data anonymization process known as the synthetic data generation, a technique becoming popular in the statistics c...
Ashwin Machanavajjhala, Daniel Kifer, John M. Abow...
Provenance in scientific workflows is a double-edged sword. On the one hand, recording information about the module executions used to produce a data item, as well as the parame...
Susan B. Davidson, Sanjeev Khanna, Sudeepa Roy, Ju...