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4 min read

28/08/2023

Sensitive Data Masking: Techniques and How to Apply Them

Masking sensitive data means changing or hiding certain elements, segments or characters of the identifiers. It means protecting personal or confidential information, while obtaining a structure and format very similar to the real one, guaranteeing the functionality of the data.

But there is a wide variety of data masking techniques. Therefore, it is useful to know which are the most used techniques and how they are correctly implemented in organizations.

 

Types of data masking

Depending on the different needs of the organization or the scenarios in which it operates, the types of sensitive data masking are mainly the following:

  • Static data masking: consists of creating a copy of the original database and, in this copy, by means of a data masking technique, the data considered sensitive is altered or disguised.
    • Typically, it is used in product development and testing/research, such as software, in order to use or share high quality original data without disclosing or compromising the sensitive data.
  • Dynamic data masking: used to hide sensitive data in transit, but without altering the original database. It is a type of real-time masking of data that is queried (read-only) by certain unauthorized users, but without overriding the actual values.
    • This type of data masking is very useful in customer query processing and information or management systems that include role-based security.
  • Deterministic data masking: this consists of the de-identification of personal or sensitive data from the tables of a database. In this data masking process, the value of a column is replaced by a certain value, which will be fixed for all associated tables.
    • For example, in a database with multiple tables, the value "Luis" is replaced with "José." Therefore, in any of the tables where "Luis" appears, it will always be replaced by "José."
  • On-the-fly data masking: in this type of processing, data is taken from the original repository to be immediately loaded or inserted, as masked data, into the target environment. In other words, it is a type of data masking in real time, during the transfer of information. 
    • For sensitive data masking, no backup copies of the original information are required. It is widely used by organizations to transfer data from one computer or department to another. For example, it is used in continuous deployment, a software development strategy, where data from the test phase must be released to the production environment.

 

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Data masking techniques

According to the different methods of hiding or disguising sensitive data, the main data masking techniques are as follows:

Substitution

In this sensitive data masking technique, identifiers are replaced by dummy data or randomly generated values from a lookup table. For example, customer names in a database can be replaced with fictitious names, or passport numbers with other random numbers.

Truncation

This consists of shortening the length of the value or sensitive data by eliminating certain characters. For example, credit card numbers can be truncated by removing some final digits and then securely storing these extracted segments in another database. 

Obfuscation

This is a data masking process in which the format or structure of the original data is modified, while preserving its meaning and maintaining its functionality. 

For example, telephone numbers or dates may be obfuscated by altering the order of the characters. However, there are many forms of obfuscation; reversible data encryption can also be applied or characters can be replaced by other characters that are very similar.

Deletion

A data masking technique that is mainly applied to documents. It consists of removing or completely deleting sensitive data and replacing it with certain predefined characters such as dashes, solid lines, asterisks, etc.  

Tags

In this data masking process, sensitive data is replaced with generic tags, assigning one tag type per field. For example, in a database, all credit card numbers are replaced by the CRED tag.

 

Recommended reading: 

6 Personal Data Anonymization Techniques You Should Know About

 

The importance of protecting sensitive data

It is important to take into account that the concept of sensitive data encompasses all information requiring protection against unauthorized access. This protection is crucial to uphold the privacy of both individuals and businesses or institutions. 

Consequently, this data is considered to include: 

  • Personally identifiable information (PII), such as passport numbers, social security numbers, medical data, biometric data, etc.
  • Business information that involves a risk to the organization, such as financial data, trade secrets, customer data, etc.
  • Information classified as secret or confidential by Public Administration entities. 

All of these types of sensitive data are part of the set of information that companies or organizations must store, manage, share and/or publish, in order to carry out their business operations, research, production, testing, etc.

This sensitive data corresponds to customers, consumers, users, patients, partners... even the organization's own finances or projects. And it is data that needs to be protected.

Why does data need protecting?

The protection of sensitive data is essential to prevent the unauthorized disclosure or publication of personal or business information and thus, ensure the privacy of the individual and entities. This, in turn, minimizes both the risk of fraud or identity theft crimes and the risk of losing customer trust.

In addition, the protection of sensitive data is necessary to comply with privacy regulations such as the European GDPR, or HIPAA in the United States. As a result, the organization avoids facing lawsuits and financial penalties that entail a high cost for the organization, both financially and in terms of image.

On the other hand, sensitive data masking and protection must be carried out to avoid exposing it to theft or to possible threats, whether they be internal or external to the organization.

 

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Discover Masker by Pangeanic

Masker is a system that uses AI to mask sensitive data. It can automatically identify personal and confidential information and then apply a range of masking techniques for protection. These techniques include substitution, obfuscation, tagging, or even adding spaces to alter, replace, or conceal the data.

This tool allows you to adjust the sensitivity level of the masking and to configure the reversibility of the process, in case it is necessary to recover the original data.

With Masker, you can store and share data securely, comply with regulations governing the protection of personal information, such as the GDPR, the HIPAA, CCPA/CPRA and APPI, and provide security for customers or users.

Masker is available in 25 languages. In addition, machine translation can also be integrated on the platform. 

Contact us for more information. At Pangeanic, we facilitate data masking processes and the protection of your company's information.

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