Final answer:
Differential privacy protects individual privacy by adding noise to a dataset, making it difficult to identify information about individuals while still sharing useful data patterns.
Step-by-step explanation:
The question asks about the technique used in differential privacy to protect individual information in a dataset. Differential privacy works by adding noise to a dataset. By integrating noise, the specifics pertaining to any individual in the dataset become less distinct, thus preserving the individual's privacy. This is essential for maintaining data utility while still conforming to privacy standards.
Differential privacy is a system for publicly sharing information about a dataset by describing the patterns of groups within the dataset while withholding information about individuals in the dataset. Introducing noise effectively makes it difficult to identify data pertaining to any specific individual, which is crucial in an age where data privacy concerns are paramount.