What Does Data Masking Software Application Accomplish?

Posted by Hridoy Ahmed on May 17th, 2021

Data privacy is of the utmost importance in this age where the influx of information appears to be as fast as the speed of light. Organizations and individuals strive to maintain their privacy without sacrificing the quality of the data that is transmitted from one source to another. In addition to data de-identification software, data masking software has also been created to meet the needs of the information technology (IT) world.

First, let's define data masking: it is the process of hiding particular items of information within a data store. This ensures that sensitive data is replaced by realistic data, and by this, we mean data that doesn't really exist. The main purpose of data masking is to make confidential information inaccessible and unavailable outside of the authorized environment. This process is generally done to provide copies of data masking snowflake to support the development and testing processes without exposing sensitive information and preventing leaks. Also, the masking algorithms are made to be repeatable to maintain referential integrity.

For data masking to be effective, the data must be modified in such a way that it is impossible to redesign or determine the actual values. Since the functional appearance of the information is maintained, the user can still test it. Data masking snowflake can also be encrypted and decrypted while setting security policies. The separation of functions between administration and security is also instituted.

You can perform data masking by using many techniques including the following:

Mix: Uses the existing data as the replacement data set and moves the values ​​such that no value appears in their original row.

Substitution: A technique that replaces existing data with random values ​​from previously prepared data masking snowflake sets.

Encryption: algorithmically encrypts the data and this technique does not make the data look realistic. Also, encryption tends to make the data bigger.

Nullification or deletion: This technique simply removes sensitive data by deleting.

Number and Date Variation: Varies existing values ​​in a specific range to disguise them.

The masking tool has some key features to achieve the following results and objectives:

• Create realistic test data that ensures the appearance of unusual patterns in the data tests.
• Serves the needs of clinical and health databases
• Takes care of massive databases in continuous mode to update test data masking snowflake cycles quickly
• To save the masking function specifications for use in other databases at scheduled intervals
• Maintains referential integrity in all tables to ensure patient information is always masked
• Ensures adversaries cannot reverse engineer data masking.
• Process large amounts of data quickly
• Masks keys to keep the same field size and type to maintain referential integrity
• Includes reference databases and templates for the most common direct identifiers.

It is important to know that masking is not enough if you really want to protect the privacy of the data source. You also need to use de-identification software to produce a very powerful combination of tools. With these two, you can quantitatively demonstrate reduced re-identification risk and ensure maximum use of information for the output data.