Anonymization is a research area that focuses on protecting the privacy of individuals by removing or modifying personally identifiable information from data sets. This process involves transforming data in such a way that the identities of individuals cannot be easily linked back to the original data. Anonymization techniques are commonly used in fields such as healthcare, finance, and social media to ensure that sensitive information is not disclosed or misused. Various methods, such as generalization, suppression, and perturbation, are used to achieve anonymization while preserving the utility and accuracy of the data for analysis and research purposes.