A hospital maintains a network of patients and doctors where edges represent consultations. To share this dataset for medical research while preserving patient privacy, which method would be most effective?

An attacker uses publicly available information to match anonymized patient records and infer a person’s illness. This is an example of:

Netflix released an anonymized dataset of movie ratings for a research competition. However, researchers were able to link records to IMDb users, revealing personal movie preferences. What was the main weakness in Netflix’s anonymization process?

A social science research institute tracks household spending habits over 5 years. To anonymize this longitudinal data, which approach is most effective?

A bank releases transaction records of its customers after applying k-anonymity. However, all customers in one anonymized group have the same income level.

Question:

A hospital releases an anonymized dataset with Age and ZIP Code as quasi-identifiers:

What is the k-value in this dataset for k-Anonymity?

In the context of dynamic data protection, what does the term "data masking" refer to?

If a dataset satisfies 3-Anonymity, what does it mean?

A company wants to protect customer purchase data while allowing meaningful insights for analysis. They apply differential privacy but notice that adding too much noise affects accuracy.

Question:

A company uses a differential privacy technique to release customer data but uses a very low epsilon (ε) value. While the data is heavily perturbed, it loses its usability for business analysis. What risk does this illustrate?