Machine Learning, Privacy, Differential Privacy, Data Analysis, Database.
Differential privacy we add noise to the input data points. So, each individual can add noise to there own data, thus eliminating the need to trust the data owner or curator at all. We can say that in this setting individuals privacy is most protected. Global differential privacy, on the other