The process of data anonymization is carried out by removing or modifying the identifying characteristics of the data. By making data anonymous, this process ensures the protection of personal information while only preserving its confidentiality without reducing its availability or functionality. The most common methods of data anonymization include masking, aggregation, and cryptography. Masking involves partially or completely hiding specific personal data by replacing it with a certain number or symbol. Aggregation involves collecting data based on a specific attribute and then analyzing it statistically, while still preserving the privacy of individual personal data. Cryptography involves encrypting data using cryptographic algorithms, making it readable only by those with a specific key. Data anonymization is important for protecting the privacy of personal information, although it may not be fully anonymous. Therefore, when selecting data anonymization methods, a proper balance must be established between protecting personal information without affecting the availability or functionality of the data.
