Data perturbation can be implemented through various techniques:
Noise Addition: Random noise is added to the data, making it harder to decipher specific details while keeping the general trends intact. Data Swapping: Elements within the dataset are swapped to anonymize the data without significantly altering its statistical properties. Aggregation: Data is aggregated into broader categories to obscure individual data points.
