What Are the Ways to Anonymize Data?

Personal data transformations are conducted in such a way that linking the data to a specific individual becomes impossible. This is the essence of data anonymization. The process aims to protect individuals' privacy by eliminating the possibility of identifying specific people based on the collected information

Krzysztof Leszczynski
Bluur® Team

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In this article:

6 most popular methods for concealing personal information

When choosing data anonymization methods, it is crucial to consider the regulations. According to the law of September 16, 2011, data anonymization involves transforming information to prevent linking it to a specific individual. This process is crucial for data transfers to law enforcement agencies of EU member states and companies processing personal data, such as employee data.

Anonymization permanently removes links between personal data and their owners. Consequently, information that previously constituted personal data loses its identifying nature, significantly enhancing individual privacy protection.

There are numerous data anonymization methods that protect personal privacy and ensure compliance with data protection regulations such as GDPR. Below are the six most commonly used methods.

6 most popular data anonymization methods

  1. Identifier Change
    Identifier Change replaces identifiers, such as names and surnames, with random or pseudonymous data during registration or logging into various online portals, especially unofficial or less trusted ones. This practice deliberately uses fictional data to protect privacy and avoid potential misuse.
  2. Data Masking
    Data Masking hides specific data segments from unauthorized persons or systems by replacing them with elements that do not reveal the original content. For instance, to enhance security, part of an identification number or credit card number may be replaced with symbols such as asterisks (*) or other special characters. This prevents full data visibility.
  3. Data Deletion or Access Restriction
    Data Deletion or Access Restriction involves the conscious and controlled elimination or hiding of information no longer necessary for processing. This strategy, also known as data minimization, protects against data breaches, identity theft, or privacy violations by removing or restricting access to unnecessary data.
  4. Data Generalization
    Data Generalization replaces detailed, sensitive information with more general, less precise values. This technique prevents identifying individuals while allowing data sharing for scientific research, statistical analyses, or health service reporting. For example, instead of using the exact age, data may show age ranges.
  5. Event Timing Shift or Delay
    Event Timing Shift or Delay modifies actual event timestamps, such as transaction dates and times, medical visits, or system logins, by shifting them by an arbitrary time interval. This technique creates ambiguity, making it difficult to identify individuals based on event sequences or specific timing.
  6. Encryption
    Encryption transforms readable information (plaintext) into an encrypted form (ciphertext) using an encryption algorithm and key. Unauthorized persons cannot understand or use the encrypted text without the appropriate key to decrypt it. Even if someone intercepts the data, they will not be able to understand it.

How to implement right data anonymization methods

Choosing the right anonymization method requires considering the specifics of the data and legal and regulatory requirements for their protection. Additionally, remember that anonymization does not guarantee complete data protection. In some cases, additional security measures may be necessary, such as using specialized software programs. By employing these, companies and institutions can safely use the information collected from users while providing appropriate privacy protection.

Krzysztof Leszczynski
Bluur® Team

Knowledge

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