The Different Methods Businesses Can Use to Mask Their Data

The definition of data masking is that it’s a technique used to protect sensitive data by replacing it with fictitious data that looks real. The purpose of data masking is to safeguard data while it is being used in testing and development environments and to prevent unauthorized access to confidential information.

Data masking can be used to protect any type of confidential information, including social security numbers, credit card numbers, and bank account numbers. There are a few different methods businesses can use to mask their data. Keep reading to learn more about each method and how businesses can use them to keep their data safe.

Substitution

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One common method of data masking is substitution, which replaces sensitive information with non-sensitive information. This can be done manually or using software that automatically substitutes values. Substitution is effective at hiding the identity of individual records, but it can be difficult to maintain consistency across multiple datasets. Substitution involves replacing sensitive information with fictitious data that has the same format. For example, social security numbers might be replaced with fictitious numbers that have the same format, such as all nine digits.

Steganography

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Steganography is a technique used to hide data inside other data. There are different methods businesses can use to mask their data, but steganography is one of the most effective ways to keep information hidden from prying eyes. By embedding secret messages into innocuous-looking files, businesses can keep their data safe from hackers and thieves. Steganography can also be used to protect trade secrets and other sensitive information. While it may not be foolproof, it is a much more secure option than simply leaving information unprotected.

Static Data Masking

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Static data masking is a technique used to protect sensitive data by obscuring it with fake or random data. Masking can be done at the time of data entry or retrieval, or it can be done as the data is stored in a database or other data repository. Static data masking is a simple and efficient way to safeguard sensitive information, and it can be used in conjunction with other security measures, such as encryption.

There are several methods for performing static data masking. One common approach is to use a pseudo-random number generator to replace actual data values with random values. This can be done either on a row-by-row or column-by-column basis. Another approach is to use a data-hiding algorithm to replace actual data values with fake data. This approach can be used to create a more consistent masking pattern.

Static data masking is a valuable security tool, but it should not be used as the only means of protecting sensitive data. It is important to remember that it can be easily circumvented if someone has access to the underlying data. Therefore, it is important to use other security measures to further protect data.

Dynamic Data Masking

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Dynamic data masking is a security feature that helps protect sensitive data by masking it as it travels outside of the secure perimeter of a company’s network. The data is masked in such a way that only authorized users can see it in its original form. This helps ensure that confidential information is not inadvertently exposed to unauthorized individuals.

Dynamic data masking is accomplished by using a variety of methods to disguise the data, such as replacing it with randomly generated values or truncating it. The masking is done in real-time, so the data is always in its original form when it is viewed by authorized users.

Dynamic data masking can be used to protect any type of sensitive information, including social security numbers, credit card numbers, and patient data. It is a valuable security tool for organizations that need to protect their data while it is in transit.

Masking Data

There are a variety of methods that businesses can use to mask their data, including substitution, steganography, static data masking, and dynamic data masking. Altogether, these methods are important for businesses to protect their data.

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