CISSP Asset Security Practice Question

Answer analysis

Option-by-option breakdown

For each option: why learners choose it and why it is or isn't the right answer here.

• ✓

  It works by adding noise to the data or query results to protect individual privacy

  Why this is correct

  Differential privacy achieves its robust privacy guarantees by systematically injecting carefully calibrated random noise into either the raw data before aggregation or directly into the query results. This noise obfuscates the contribution of any single individual, making it statistically difficult to determine if a particular individual's data was included in the dataset or query. This method allows for the release of aggregate statistics while mathematically bounding the risk of individual re-identification, balancing utility and privacy.

• ✗

  It ensures that no individual's data can ever be inferred from the released statistics

  Why it's wrong here

  While differential privacy offers a strong, mathematically provable guarantee against re-identification, it does not promise absolute zero inference of individual data. Instead, it quantifies and limits the maximum amount of information an adversary can learn about an individual by observing the output, regardless of their auxiliary knowledge. The guarantee is probabilistic, ensuring that the presence or absence of any single individual's data in the dataset has a negligible impact on the final aggregate output, thereby limiting the risk of specific attribute inference.

• ✗

  It requires that data be encrypted before release

  Why it's wrong here

  Differential privacy is a technique focused on obscuring individual contributions within aggregate data through noise addition, which is distinct from data encryption. Encryption is a cryptographic method primarily used to protect data confidentiality during storage or transit, rendering it unreadable without a key. While both are privacy-enhancing technologies, differential privacy operates on the statistical properties of data release, whereas encryption secures the data itself, and one does not inherently require the other for its function.

• ✗

  It is a method of pseudonymization that replaces identifiers with pseudonyms

  Why it's wrong here

  Pseudonymization is a data de-identification technique where direct identifiers are replaced with artificial identifiers or pseudonyms, aiming to reduce the linkability of a data set to an individual. Differential privacy, however, does not primarily involve replacing identifiers; instead, it directly modifies the statistical output or the underlying data by adding random noise. These are distinct privacy-enhancing methods: pseudonymization changes identifiers, while differential privacy perturbs data values to prevent inference.

Go deeper

Related to this question