Option A: Differential privacy is a technique used to protect individual privacy when analyzing aggregated datasets by adding random noise. This ensures that the privacy of individuals in the dataset is preserved because the noise obscures the data of individual users while still allowing for overall trends and patterns to be analyzed.
Option B: Assessing differences between datasets does not accurately describe differential privacy.
Option C: Applying asymmetric encryption to datasets is a security measure, not specifically related to the concept of differential privacy.
Option D: Removing personal identifiers is related to de-identification or anonymization, but differential privacy specifically involves adding noise to maintain privacy in statistical outputs.
References:
IAPP CIPT Study Guide
NIST Differential Privacy Overview
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