Data security is keeping data protected from corruption and unauthorized access. Data security focuses on ensuring privacy while protecting personal or corporate data using Data masking and Data Encryption.

Do you need clarification on Data masking and Data encryption?
Well, within the data community, encryption is considered a form of data masking. Though many would identify both as the same, Data masking and Data encryption are two technically distinct processes for data security.

At the same time, there are few similarities between data masking and data encryption, although the differences are substantial. Each is designed to ensure data security, which can be substantially improved when both are used in synergy.
So, what is the basic difference between masking and encryption?

Encryption is a reversible process where masking reversibility is hard.

Data Masking

In my tenure, I have worked on many projects and handled sensitive data to perform research and development tasks. Passing sensitive data through many hands is at great risk of theft or misuse. The important elements of the data set, such as names and addresses, are protected through redacting (stripping, covering over, or removing). This process, however, is often irreversible.

There are many tools in the market to mask the data. In the past, I have used the Informatica ETL tool to mask sensitive data using Data Masking transformation. The same can be achieved using the alter column and setting the ‘Masked’ function on the column level in SQL. Data masking using the SQL Masked function is preferred as it is an easy method. I like dedicated masking tools like Delphix or ETL tool for complex masking.

Data Encryption

It is a process used to protect data that transfers between computers or networks so that it can be decrypted later. Data is extremely vulnerable to a breach. Conversion of data into non-readable gibberish creates highly secure results. The only way to access the data is to unlock it with a key or password, which can only be accessed by those authorized.

For example, In a database, the EncryptByPassPhrase(‘passcode,’’ Value’) function will convert the value into encrypt format to read the encrypted value. DecryptByPassphrase (‘passcode,’ ‘Encrypted value’) function will restore its original value.

Note: passcode should remain the same while encrypting and decrypting value.

To summarize, if you want to protect your production data from unauthorized entry, it is important to use encryption and decryption methods in its current context. However, if you need to use your production data in a test environment where the actual content of the data is meaningless, then use masking.

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