Security Guards Are Not Just for Celebrities

The Six Main Techniques Used In Data Masking

26 May 2016 by Deann Collins

Data masking is used to hide sensitive data from potential security breaches. This is done through the use of any of six techniques that have been devised to make it possible for entities relying on database systems to store data to secure information. 

To arrive on the most efficient and effective method of masking sensitive data, it's important to understand the different techniques available. The following is an explanation of each of the six data masking techniques:

Substitution

Substitution allows data to be masked while also leaving data records with an authentic appearance. This data masking technique involves switching sensitive data with alternative values that fit into a certain data field type. 

Substitution is a good choice for data masking needs that involve fairly large data subsets. It works well for masking numerical data like customer payment information or social security numbers, for example. 

Shuffling

Shuffling is similar to substitution, but it involves moving around the data that's already present rather than completely replacing it. Shuffling is not always as secure as substitution. It is sometimes possible for intruders to discover the shuffling algorithm that was used to translate the shuffled data back to the original data being masked. 

Encryption

This is a highly complex method of data masking that involves the creation of an encryption algorithm. This algorithm puts a "lock" on the data that can only be reversed using an algorithm "key". 

Nowadays, the most secure type of encryption data masking is known as format preserving encryption, or FPE. This type of encryption will not only mask sensitive data, but also preserve any entity properties so that information is not lost during the encryption process. 

Masking out

Masking out involves scrambling individual characters so that original data is protected from potential security breaches. This is a commonly used data masking option for protecting credit card data by hiding all but the last four digits, for example.

Deletion

With deletion, sensitive data is hidden by using a null value in certain fields. Deletion can only be used for data masking in fairly limited situations. For example, it is appropriate if the only thing that needs to be protected is the data element itself. Deletion can harm data integrity and is somewhat weak because masked data could potentially be stolen through reverse engineering. 

Variance of dates and numbers

Masking data using number and date variance will create a situation where the original data is altered but still appears as if it is unmasked. The resulting masked data is imprecise but still is close enough to the correct data to show general trends and tendencies in the original data. However, any unauthorized party accessing the data will not be able to tell that the true data has been masked over. Contact a business, such as Info Incognito for more information. 

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