The Difference Between Data Masking and Data Encryption

Whats the difference between data masking and data encryption, and which should you use to meet your data protection needs?

Deciphering Which Data Protection Strategy Is Best for You

More than 95% of web traffic is encrypted. But a huge amount of data is masked.

Which do you need: data masking or data encryption?

Before you jump into one or the other as a strategy of protecting your sensitive data from being hacked, manipulated, or stolen, it’s going to pay you to understand the difference between data masking and data encryption.

Encryption vs. masking ─ a question of data security

In the modern world, it’s crucial to protect your data.

First, from a compliance point of view. In many cases, there is a legal obligation to secure private information, such as that handed down by the General Data Protection Regulations (GDPR) in the European Union.

Second, it’s simply good business practice, isn’t it? I mean, would you want to deal with an organization that doesn’t care enough about its customers or members to protect their information? Nope, neither would we.

Two ways to help protect your data are masking and encryption.

So, what’s the difference between encryption and data masking?

When you encrypt your data, you transform it into unreadable gobbledygook. It can only be deciphered by someone who has the decryption key to do so. If you don’t have the key, the data you have is useless.

Now, data masking doesn’t create a meaningless mess. Instead, it produces a fictional depiction of data in the same format but that doesn’t divulge any meaningful information. You know when you pay for your shopping or gas by credit card, and the receipt shows your credit card number as something like ‘XXXX XXXX XXXX 1007’? That’s an example of data masking. You cannot get back the actual data.

When would you use data encryption?

Let’s get down to the practical details. If you encrypt data, it makes that data useless to a hacker, unless, of course, that hacker gets hold of the encryption key. Then you’re in trouble.

So, surely, it’s better to use data masking, isn’t it?

It depends on what you are doing with the data.

For example, let’s say that you need to transfer some information that the recipient must be able to read. Without the information, the recipient won’t be able to complete the task needed. There are lots of examples in everyday life, such as:

ATMs (your information is sent in an encrypted form to protect it in transit)
Online payments (when your card details are protected by encryption)
Messaging apps (you don’t want your message to be intercepted and read, but you do want the intended recipient to make sense of it)

Data at rest should also be encrypted. While it is not currently being used, the information cannot be ‘destroyed’ as it would be by masking, because it will be needed at some time.

When is data masking useful?

Okay, so now you may be wondering why you shouldn’t just use data encryption? Simply put, while encryption is very safe, it’s not 100% hack-proof. Of course, sending fictional information (as you would when data masking) is hack-proof ─ but useless if you need the information, as we established above.

If you don’t need the actual data, but require fake but functional data to use as placeholder data, then data masking is the way to go. Like on that shopping receipt.

The benefits of data masking include:

Data masking eliminates critical threats, including account compromise, insider threats (71% of cybersecurity incidents in healthcare involve employees), and poor systems interfaces with third parties.
Data risks in the cloud are also reduced.
Data masking is particularly useful if you need to develop or evaluate systems while maintaining the integrity of your data.
If you are sanitizing data on your system, then masking it will replace existing information and remove all traces of the previous data.

Methods of data masking

There are several methods that can be employed to mask your data. These include:

Data scrambling

The characters in a piece of information are scrambled. For example, an account number that reads 5623890147 could be scrambled to read 7642130859. Scrambling is simple to perform but is limited in use and less secure than other masking methods.

Value variance

This method replaces the original data with a function. An example might be when an investment portfolio has its exact purchase prices replaced by a range of prices paid.

Data substitution

Here, the values or characters are replaced by fakes (which must be realistic). For example, customer names may be replaced by fake names.

Pseudonymization

Here’s an innovative word for you! Introduced by GDPR, pseudonymization is the process that masks a person’s real identity. It removes real names, dates of birth, etc., and replaces them with fake information so that the person cannot be identified through a combination of data.

Which is right for you: Data masking or data encryption?

How do you decide which one is right for you?

Most companies require both encryption and masking strategies. You should consider the following factors:

What information must be protected
The applications that use the data to be protected
Where the data resides
Who is authorized to view the data

If you are employing data masking, then you should use the same algorithm for specific types of data ─ and ensure that the most suitable method is used for each category of information.

You should also consider your budget, regulatory requirements, and in-house admin and IT functionalities.

Finally, it is crucial that you not only secure your data effectively but secure how you secure your data. Who will be authorized to have access to your scrambling algorithms, for example? If this information gets out, then your masked data can be reverse-engineered ─ and your investment in data security will be wasted.

Data encryption vs. data masking: The key takeaways

Data encryption is the process of converting data into a form that cannot be read by anyone who does not have access to a decryption key.
Data masking is the process of replacing sensitive data with realistic but fictitious information so that the original data cannot be traced.
Encryption is crucial for data security when actual information is critical to effective operations because it can reduce the damage caused by security breaches. This is especially relevant for companies operating in critical industries (such as finance, healthcare, and education) where encryption is mandatory under law.
Depending on the type of data masking used, your data could be 100% protected ─ because it no longer exists except as a fake dataset. Perfect if the actual data is not needed.
When planning and implementing encryption and masking, consider the project from the ground up. Ask why, how, who, when, where ─ and ensure that you budget effectively.