What is the difference between differential privacy and anonymization?

What is the difference between differential privacy and anonymization?

Differential privacy is a technique that ensures individual data points cannot be identified, even when data is shared. Anonymization, on the other hand, involves removing personally identifiable information from data sets, but it can sometimes be reversed.

Can you give an example of how differential privacy works?

Sure! In a survey, if you want to share the average age of participants without revealing individual ages, differential privacy adds random noise to the data, ensuring that the average remains accurate while protecting individual identities.

Is anonymization enough to protect user data?

Not always. Anonymization can be vulnerable to re-identification attacks, where attackers use other data sources to identify individuals. Differential privacy offers stronger guarantees against such risks.

Which method is more commonly used in data sharing?

Anonymization is more commonly used due to its simplicity, but differential privacy is gaining traction, especially in sensitive data contexts.