Pseudonymization refers to processing in accordance with a specific meaning in data protection**. This may be different from how the term is used in other contexts, industries, or fields. Article 4(5) of the UK Data Guard** defines pseudonymization as: "...Personal data are processed in such a way that personal data cannot be attributed to a specific data subject without the use of additional information, provided that such additional information is retained separately and is subject to technical and organizational measures to ensure that personal data cannot be attributed to an identified or identifiable natural person. ”
At a basic level, pseudonymization starts with one input (raw data) and ends with two outputs (pseudonymized dataset and additional information), and it refers to technology that identifies personal information by replacing, deleting, or transforming. For example, replace one or more identifiers that can easily be associated with an individual, such as a name, with a pseudonym, such as a reference number.
Yes. Pseudonymization can reduce the privacy risks faced by individuals. Helps data controllers and processors meet their data protection obligations, including data protection design and security. However, when the data controller and processor process the data in this way, he does not change the status of the personal data.
Data Protection** clearly states that information is personal data if a person can be identified or identifiable, directly or indirectly. The general processing regime also makes it clear that pseudonymized data remains personal data. For example, the UK General Data Protection Regulation (GDPR) Recital 26 states: "Personal data that have been pseudonymized shall be deemed to be information about another natural person if it can be identified by means of additional information." ”
There can be confusion between pseudonymization and anonymization. For example, people often refer to a dataset as "anonymized data" when it still contains personal data, but only in anonymized form. Although pseudonymization reduces the risk of personal data and measures are taken to make individuals less identifiable, it is still considered a form of processing of personal data. Pseudonymized data can still be associated with a specific individual through additional information. However, anonymization is a stricter processing process designed to make it impossible for personal data to be associated with any specific individual. The process of anonymization makes personal data so unrecognizable that it is impossible to re-identify the individual by any means. The anonymized data is no longer considered personal data because it can no longer be associated with a specific individual.
Data Protection** is clearly stipulated:
Anonymous information is information that is not associated with an identified or identifiable individual (and the law does not apply to such information).
Pseudonymized data is still personal data.
It is important to understand this distinction. Through pseudonymization, the correlation between individuals and the data associated with them is reduced, but not completely eliminated. Although individuals may not be able to be identified from the pseudonymized data itself, they can still be identified by referring to other separately held information. Therefore, the dataset and additional information are still personal data.
Pseudonymization can help achieve the following goals:
Reduce the risks posed by the processing of individual rights. Pseudonymization can reduce the risk of direct identification of personal data. By separating personal identifiers from data, pseudonymization can reduce the risk of misuse or unauthorized use of data, thereby enhancing the privacy protection of data subjects.
Enhance the security of the processing of personal data. Pseudonymization helps improve the security of your data. By reducing the direct association with an individual's identity, pseudonymization can reduce the risk of a data breach. Even if pseudonymized data is accidentally obtained, it is difficult to re-identify it as a specific individual, increasing the security of the data.
Useful for data research and analysis. Pseudonymization allows data to remain usable to a certain extent, while reducing the invasion of personal privacy. This allows organizations to use pseudonymized data for analysis, research, and insights to derive valuable information from it, without having to directly access and process raw personally identifiable information.
Support overall compliance with data protection principles. Pseudonymization helps meet data protection and compliance requirements. Many data protection** impose strict requirements on the processing and protection of personal data, and pseudonymization can be used as a compliance measure to reduce risks during data processing and ensure compliance with legal and regulatory provisions.
Pseudonymization can improve the usefulness of data to a greater extent than anonymization. However, the data controller should still consider whether anonymous information can be used to achieve your goals. As a data controller, it is your responsibility to decide whether and how to implement pseudonymization techniques. Therefore, it is important to clearly define the scope, parameters, and objectives, as well as possible risk scenarios.