Differential privacy: adding noise to a data set, which makes that data set less useful
Crowd-blending privacy: It involves limiting how a data set can be analyzed to ensure that any individual record is indistinguishable from a sizeable crowd of other records—and removing a record from the analysis if this cannot be guaranteed.