As data use has become ubiquitous in recent years, data breaches have followed suit. In 2021, the Identity Theft Resource Center recorded more than 1,800 instances of compromised data, a 68% increase over 2020 and 23% rise from the previous all-time high. By October of 2021, the total number of data breaches exceeded all of 2020, and the people affected by those breaches in the third quarter alone outnumbered the first two quarters combined.
The bottom line is that collecting, storing, and using data inherently introduces the risk of that data being compromised. To avoid imminent damages to an organization’s reputation, trustworthiness, and revenue, many are turning to data obfuscation to preserve data’s privacy and security.
In this blog, we look at what data obfuscation is, the benefits of using it, the most common techniques, and the capabilities data owners should look for when selecting a data obfuscation tool.
What Is Data Obfuscation?
Data obfuscation is the process of scrambling data to obscure its meaning, providing an added layer of protection against threats and malicious actors. By hiding the data’s actual value, data obfuscation renders it useless to attackers while retaining its utility for data teams, particularly in non-production environments.
For developers using potentially sensitive customer or company data to build and test applications in non-production environments, the ability to access quality data is critical. However, these non-production environments often do not have sufficient security perimeters or access controls in place – leaving data vulnerable to attack. Data obfuscation allows developers and testers to access realistic data, but since it no longer contains personally identifiable information (PII), they can do so without the concern of it being exploited.
The Benefits of Data Obfuscation
As noted above, one of the top benefits of data obfuscation is its ability to secure non-production environments and minimize risks when building new applications and programs. This is powerful for organizations looking to gain a competitive edge with innovative new technologies or product features.
Another primary benefit of obfuscating data is that it enables secure data sharing. In today’s global marketplace and increasingly connected world, sharing data both internally and externally is a key business driver, and has been linked to increased stakeholder engagement and enterprise value. The ability to obscure sensitive data makes it easier to securely share across lines of business or with third parties without risking unauthorized access.
Now more than ever, data sharing and data use more broadly must be compliant with an ever-growing list of regulatory requirements, data use agreements, and internal company rules. The EU’s General Data Protection Regulation (GDPR), for example, is quite strict about the use of personal data. Data obfuscation helps organizations overcome that potential hurdle by altering PII, thereby mitigating their risk of incurring fines or of any real damage should a breach occur.
Data obfuscation also enables self-service data access by allowing data teams to develop, test, analyze, and report on data, without having to jump through hoops to get the data needed to do so. This makes data supply chains more efficient by reducing the burden on IT and data engineering teams to manually respond to every data access request. Organizations can be confident that self-service data use doesn’t come at the expense of customers’, employees’, or users’ data privacy.
Data Obfuscation Techniques
With this foundational understanding of data obfuscation and its benefits, let’s look at three of the main techniques used to obfuscate data: data masking, data encryption, and data tokenization. Here, it’s worth pointing out that while encryption and tokenization are reversible (the original values can be derived from the obfuscated data), data masking is not.
Data Masking
Data masking is a data security measure that involves creating a fake but highly convincing version of an organization’s secure data. The idea is to protect data from breaches or leaks in instances where functional data sets are needed for demonstration, training, or testing, without revealing actual user data.
Essentially, data masking uses the same format as existing databases, but changes datas’ values. This process is done in such a way that the data cannot be reverse-engineered to reveal the original data points. Numbers and characters may be scrambled, hidden, substituted, or even encrypted.
Data Encryption
Encryption can be thought of as a form of secret code, which scrambles the relevant information in a set of data and can only be reversed by assigned parties who possess the necessary encryption key. In asymmetric encryption, one public key and one private key are required to decrypt the data, while in symmetric encryption, just one private key is necessary for encryption and decryption. Either way, the data can’t be manipulated, analyzed, or used in any way until it’s decrypted.
Data Tokenization
Tokenization is a specific form of data masking where the replacement value, also called a “token,” has no extrinsic meaning to an attacker. Key segregation means that the key used to generate the token is separated from the pseudonymized data through process firewalls. The token is a new value that is meaningless in other contexts. Importantly, it’s not feasible for an attacker to make inferences about the original data from analysis of the token value.
Other Data Obfuscation Techniques
While the techniques cited above are the most common, others exist as well. Nulling, for example, replaces part of the data with null-valued variables, while blurring offsets the values of certain data by a predetermined amount. Meanwhile, as the name implies, randomization involves randomly reordering characters and numbers.
What to Look for in a Data Obfuscation Tool
When looking for the right tool to help you obfuscate your organization’s data, there are several factors to consider. Chief among them is whether or not the tool you’re considering has the right capabilities. Specifically, you’ll be best served with a tool that enables:
Sensitive Data Discovery and Classification
The best data obfuscation tools automatically scan cloud data sources, detect sensitive data, and generate standard tagging across multiple compute platforms. With sensitive data discovery, you can eliminate manual, error-prone processes and get universal data access control and visibility into your most sensitive data.
Attribute-Based Access Control
You’ll also want to ensure that your data obfuscation tool empowers your data teams to create automated policies to govern cloud data use. Dynamic attribute-based access control will allow you to scale user adoption, eliminate approval bottlenecks, and build trust with compliance and governance teams.
Automation
Being able to automate the data obfuscation techniques mentioned above is also important. Dynamic data masking and anonymization with mathematical guarantees can accelerate data sharing use cases, as well as enable data engineers and operations teams to automate data access control across your entire cloud data infrastructure at scale.
Data Policy Auditing
Finally, make sure that any data obfuscation tool you choose captures data policy enforcement in rich audit logs so that it’s easy for your data teams to keep track of data security compliance laws and regulations. This is critical for ensuring that obfuscation is working as intended, and can identify any suspicious activity immediately.
Immuta empowers data engineering and operations teams to automate data security, access control, and privacy protection. Our industry-leading automated data access solution offers data obfuscation capabilities to help any organization ensure its data use is secure, compliant with the latest regulatory requirements, and self-service for maximum efficiency.
To see how Immuta can simplify data masking and access control, start a free trial.
