It’s no secret that companies handle sensitive data daily. This data could be from customer credit card numbers to employee social security numbers. To protect this data, companies often use a process called data masking. Data masking is a technique to protect sensitive data by replacing it with surrogate data. It aims to prevent unauthorized access to confidential data while being used in a test or development environment. It’s also used to protect personally identifiable information (PII), such as social security numbers, credit card numbers, and driver’s license numbers. There are several data masking methods, but the most common is to replace confidential data with random values. Keep reading to learn more about data masking and how it can help keep your data safe.
Data Mask Techniques
A data mask transforms sensitive data into an unreadable format. This process can protect confidential data while being used in a testing or development environment. Masking can also hide personally identifiable information (PII) from unauthorized individuals.
Several different methods can be used to mask data. One common approach is to replace sensitive data with random values. This can be done manually or using a computer algorithm. Another method is to encrypt the data using a robust encryption algorithm, making data difficult to read. A third approach is to use a data obfuscation tool. This type of tool scrambles the data so that it’s not possible to read it without the proper decryption key. This approach is often used to protect PII.
The masking used will depend on the organization’s specific needs. It is essential to select a method that provides the desired level of security without compromising the system’s performance.
Clean and Prepare the Data
The data masking process is an integral part of protecting sensitive information. This can involve removing any identifying information, such as names and addresses, and formatting the data to be ready for masking.
The first step in the data masking process is the cleaning and preparing the data. The next step is to obscure the data. This can be done in several ways, including substitution, deletion, and encryption. Substitution involves replacing sensitive data with non-sensitive data. Deletion involves removing sensitive data altogether. Encryption involves transforming data into an unreadable format. The final step is to secure the data. This can involve protecting it with passwords or other security measures.
Software-based masking is an automated process that replaces sensitive information with random values known as tokens. Tokens are meaningless to anyone who may access the data, but they retain the same format as the original values so that reports and analytics can still be generated.
Types of Data Protection
There are two main types of data masking: Static and dynamic. Static masking is a more straightforward process involving replacing all sensitive data with a single value. Dynamic masking is more complex and can replace individual bits of information on a case-by-case basis.
With static data masking, the data is masked when first entered into the system. This means that the information is hidden from all users, including administrators. Static data masking is an excellent way to protect not regularly accessed data. With dynamic data masking, the data is masked as it is accessed. This means that the information is hidden from authorized users, but administrators can still see it. Dynamic data masking is an excellent way to protect sensitive data that is regularly accessed.
The masking process can be used in several ways, depending on the organization’s needs. It can protect against accidental disclosure, unauthorized access, or malicious attacks. Masking can also help organizations comply with regulations such as GDPR and HIPAA. This is an important security measure that should be implemented to protect sensitive data.
