How does differential privacy ensure security?

What is differential privacy and how does it work?

Differential privacy is a technique that ensures individual data privacy while allowing for data analysis. It adds noise to the data, making it difficult to identify specific individuals.

How does adding noise protect individual data?

By adding noise, the data becomes less precise, which means that even if someone tries to infer information about an individual, the results will be unreliable.

Can you give an example of differential privacy in action?

Sure! A common example is when a company collects user data to analyze trends. They can share aggregated results without revealing any individual's data by applying differential privacy.

Are there any limitations to differential privacy?

Yes, while it provides strong privacy guarantees, it can sometimes reduce the accuracy of the data analysis, especially if too much noise is added.