Gyoumagazine
Typically, differential privacy works by adding some noise to the data. Imagine it like pixelating a face to hide someone's identity. The amount of noise added is a trade-off – adding more noise makes the data more anonymous, but it also makes the data less useful.
- How would you define differential privacy?
- What is differential privacy on Iphone?
- What is Delta in differential privacy?
How would you define differential privacy?
Differential privacy is a system for publicly sharing information about a dataset by describing the patterns of groups within the dataset while withholding information about individuals in the dataset.
What is differential privacy on Iphone?
It is a technique that enables Apple to learn about the user community without learning about individuals in the community. Differential privacy transforms the information shared with Apple before it ever leaves the user's device such that Apple can never reproduce the true data.
What is Delta in differential privacy?
(2) Delta (δ):
It is the probability of information accidentally being leaked. If δ= 0, we say that output M is ε-differentially private. Typically we are interested in values of δ that are less than the inverse of any polynomial in the size of the database.
