Static Data Masking (SDM)

Static Data Masking (SDM) is also known as Data Masking and is one of the most underrated terms in Data but at the same time it's one of the most wanted terms for Data Privacy.

Let’s decode it….

Data Masking is from the same family i.e., Data Perturbation/ Swapping/ Shuffling/ Data Scrambling/ Data Obfuscation.

Data Masking is a technique to convert actual data into dummy data for the sake of hiding its originality. If the Credit Card number is 3345-0987-2234-2342, it will be converted into 1234-5678-9101-1123. So, if someone can view my data, my identity will not be disclosed. I am sure understanding of Data Masking is not difficult but the implications of not having or having bad techniques are debatable.

Please note, there are many domains where Regulatory bodies don't allow organizations to disclose certain sets of data to anyone which creates challenges in the development environment or at the time of sharing the data to third/ external parties.

If you don't have proper Data Masking tools and techniques, there is a chance to get penalties from Regulatory bodies.

There are two Data Masking approaches 1) manual 2) automated.

In MANUAL approach, password is changed in ***** or date is converted into 01/01/9999 etc. using manual queries but reverting to original data is not possible. This approach is used to pass Masked data to development teams where reverting back is not required.

During the era of ONLY Structured data, as data was not huge, Manual approach was practicable but with the introduction of semi and unstructured data coming from social media, CCTV, Sensors, Audios etc., one must opt for Automated Approach.

Within the AUTOMATED approach there are 2 ways.

1.    Data is masked using scripts so it can be reverted to its original condition once the purpose is served e.g., you want to give data set to another organization using an external drive or via public hosting, in this case data is masked and once data has reached to the destination it’s revertible to its original condition for their decision making.

2.    There are tools that mask data across the whole data model e.g., if the Credit Card field is present in 10 different tables, these tools make sure 3345-0987-2234-2342 is converted into 1234-5678-9101-1123 in every table. This will assist in maintaining the essence and relationships of data even after masking.

In a nutshell, the way data is growing and the way the world is moving towards Cloud, Data Masking has become inevitable.

Cheers.