The Difference Between Data Masking and Data Obfuscation

Does your company control who can see specific data in all of your applications?

This question is the simplest, most foundational one you’ll encounter in data security. However, if you were to ask people what they were doing, very few could offer a comprehensive response around their strategy.

Controlling access to sensitive data is an ongoing challenge for risk, security, and compliance professionals. Some companies deploy a complex blanket defense that limits what people can see; others restrict apps entirely. Both of these approaches introduce key pain points: they’re difficult to implement, and they’re not foolproof—any data that’s not labeled properly won’t be hidden behind these solutions. 

Some better options include data masking and other types of data obfuscation. People often use these terms interchangeably, and they’re both methods companies use for data access control and user privacy. They’re not quite the same, though, and knowing the distinction can help you make better decisions for your company.

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Data Obfuscation vs. Data Masking

Data obfuscation is the blanket term for transforming data into a different form to protect it. There are three main types of data obfuscation: data masking, tokenization, and encryption.

Data masking creates a substitute version of a dataset. The data values are changed, but the format remains the same. Because of this, an organization can run tests or training sessions as if it were using the real data without actually compromising that user information. Recent legislation such as the General Data Protection Regulation (GDPR) and the California Consumer Privacy Act (CCPA) has highlighted the need to protect user data, and data masking offers a solution.

Beyond data masking, another form of data obfuscation that many IT teams also use is tokenization, another irreversible process that replaces sensitive data with meaningless values. This technique is beneficial in financial institutions or retail stores, which can take credit card payments without displaying the real data to a third-party processor.

Encryption is another common data obfuscation technique, translating data into a different form that only people with a password or decryption key can access. Encryption is more cumbersome than data masking because you can’t analyze the data while it’s encrypted. Most organizations use encryption for data at rest and in motion.

The biggest problem with these data obfuscation methods is that they must be deployed, which adds a layer of complexity for internal teams. That might mean some type of integration, either through standing up another server or application to run in a separate environment. Or perhaps there’s a proxy agent involved, which means that a company needs to worry about device controls or deploying to endpoints.

As a result, there’s often a patchwork of obfuscation efforts instead of a single solution that can easily limit access to the data to ensure users only see what they need to in any given app. 

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Why Data Masking is Important

Cyber attackers are going after identities in the cloud at a higher rate than ever before—and companies are struggling to keep up. Gartner predicts by 2023, inadequate management of identities, access, and privileges will result in 75% of cloud security failures.

What’s more, Gartner notes that because sophisticated threat actors are targeting identity and access management (IAM) infrastructure, the misuse of credentials is a primary attack vector. Even with an increase in resources and training, human error remains a consistent factor in the majority of data breaches. Awareness campaigns aren’t getting the job done, so companies must try a different approach. If an organization can show users only what they need to see, then it is less likely that sensitive information will fall into the wrong hands.

While you could mask just about any dataset, this technique is most useful when dealing with PII or other sensitive information. Exposing data such as credit card or social security numbers, health insurance information, home addresses, or banking information can lead to severe repercussions. Since different people within the organization don’t actually need to see that data to do their jobs, data masking becomes an essential security component.

Perhaps the biggest challenge with data masking is changing the data enough to prevent anyone from figuring out the authentic information without transforming the characteristics of the original data itself. The original values of masked data are permanently stripped (if the data masking is done correctly), with no way to recover them.  

The Smarter Way to Protect Company Data

Data obfuscation and data masking are preferable to restricting access to entire apps and databases, which disrupts worker productivity and can spur them to try and get into those apps and databases in less secure ways.

However, data obfuscation only works well if it’s set up correctly and, ideally, won’t add extra complexity and strain to your security and compliance teams.

Nullafi’s proprietary data obfuscation protocols address the problems that a perimeterless world presents, such as data leakage, tampering, improper downloading, and more. We intelligently recognize and mask sensitive data in transit before it gets to a user’s device, no matter its origin, field, or label. 

There’s no need to install extensive, complex software, deploy app updates, or go through hours of confusing training. Nullafi software is delivered as a containerized service. Deploy it with a simple script and use our controls to manage, monitor, and block data access for any user in any application.

Get started protecting sensitive data—no matter where it lies within your organization. Request a demo today.