VARCHAR in SQL data masking

02 Oct 2023

dataMasking

Data masking is a technique used to obfuscate sensitive data in a database, ensuring that only authorized individuals can access the actual values. One commonly used method for data masking is using the VARCHAR datatype in SQL.

In SQL, the VARCHAR datatype is commonly used to store variable length character data. It allows a maximum length to be specified, accommodating a range of character values. When applying data masking techniques to VARCHAR columns, there are a few approaches that can be used:

Partial Masking: Partial masking involves replacing a portion of the original value with a masked value, while keeping the rest of the data intact. For example, if we have a VARCHAR column storing email addresses, we can mask the domain part of the email address, while leaving the username visible. This can be accomplished using SQL string manipulation functions like SUBSTRING or CONCAT.
```
UPDATE users
SET email = CONCAT(SUBSTRING(email, 1, INSTR(email, '@')), '[MASKED]')
WHERE user_id = 123;
```
Full Masking: Full masking involves replacing the entire original value with a masked value. This is useful when the entire value needs to be hidden. For example, if we have a VARCHAR column storing social security numbers, we can fully mask the value by replacing it with asterisks. The length of the original value can be determined using functions like LENGTH or CHAR_LENGTH.
```
UPDATE customers
SET ssn = LPAD('', CHAR_LENGTH(ssn), '*')
WHERE customer_id = 456;
```
Hashing: Hashing is another form of data masking that involves transforming the original value into a fixed-length string using a hash function. This technique is irreversible, meaning the original value cannot be obtained from the hashed value. Hashing is commonly used to mask sensitive information like passwords or credit card numbers.
```
UPDATE accounts
SET password_hash = SHA256(password)
WHERE user_id = 789;
```

By using VARCHAR columns in SQL and applying appropriate data masking techniques, we can effectively protect sensitive information from unauthorized access. By obscuring the actual values, data masking helps to maintain data confidentiality and comply with privacy regulations.

#dataMasking #SQL