There’s an old adage that all press is good press, but one kind of attention that’s been showered on companies both large and small in recent months is the type that no organization wants — scorn after an inadvertent data leak.
While keeping customer data safe from leaks may seem complicated, there are certain tools that are simple to implement and don’t affect your day-to-day operations when managed effectively. One of those tools is data redaction.
Put simply, data redaction refers to the removal of certain pieces of information from data, designed to keep that data from being linked to specific people or used for nefarious purposes.
For the most well-known popular culture example of redacting, think of spy movies where the hero flips through documents which have had large portions crossed out with black ink. Those portions have been redacted, and businesses everywhere today do the same thing within the digital space.
Redaction vs. Masking
While data redaction is a commonly used method in data security, it can sometimes be confused with a related concept known as data masking. But what exactly is dynamic data masking, and how does it differ from data redaction?
With data redaction, sensitive, confidential, or personally identifiable information is simply removed — in some cases, it’s literally blacked out.
With data masking, however, data isn’t just removed — it’s either replaced with a sort of placeholder data point that’s either randomly generated or created using a set of parameters designed to ensure anonymity, or it’s generalized to the point that it can’t be used to identify someone.
For example, let’s say that one individual in a data set appears as “Male, age 28, zip code 84062.” Using data redaction, the data point may look like this:
“Male, age —, zip code ——”
In this case, identifying data has been removed entirely. But data that has been masked may look like this:
“Male, age 20-30, region Utah”
Both can be effective when used correctly, but they’re distinct in exactly what they mean and how they’re implemented.
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Why is Data Redaction Important?
The average organization deals with a range of data types, including employee data, customer data, and company data. Each of these data types offers up fairly obvious reasons as to why it needs to be protected from leaks, breaches, or unauthorized access. Leaked customer data can lead to legal ramifications, loss of trust in your business, government fines, and of course the ethical failure of putting your customers in harm’s way. Leaks of employee data can lead to many of the same issues, while leaks of company data can provide valuable insights for your competitors, as well as release proprietary information that’s better kept private.
One of the most effective ways to limit the unauthorized access of data is to limit the authorized access of data — determining who is allowed to access which data points. Data redaction, at its essence, is simply one form of limiting access. By redacting unnecessary information before it is accessed or used by a party, you can limit the identifying information and other sensitive data that’s shared, mitigating risk of leaks and breaches throughout your organization.
When Do I Need to Redact Data?
When you need to focus on data redaction will depend on your company, industry, data types, and data management approach. However, there are some general handoff points and events which could benefit from data redaction in order to help keep your business, employees, and customers as safe as possible. Here are five of the most common times when data redaction can be of service to your organization, as well as details about how best to handle data redaction in each individual case.
When Acquiring Data
One of the best times to redact data is immediately upon receiving it, before it can be disseminated to other sources and increase the potential for leaks. When you receive a data set or report, consider immediately redacting any information that’s not directly relevant to the work that you or employees who will view the data are doing.
With the right data management tool, such as Immuta, certain data points can be automatically redacted to streamline your process. Other data can then be manually redacted on a case-by-case basis.
For an added layer of security, a data security specialist at your organization can check your redacted outputs to ensure that all sensitive, non-essential data has been redacted before the report or data set is shared throughout your organization or team.
Before Distributing Data
If there’s data in your reports that doesn’t have use in any context within your organization, it can safely be redacted immediately upon receiving it. But what about data that may be applicable to some groups or individuals within your organization, but not others?
Rather than redacting this information upon acquisition, you’ll want to redact sensitive data before it’s distributed to relevant stakeholders. For example, if certain engineering data isn’t relevant to a financial arm of your organization, you may redact that information before distributing it to that particular team. Data access control solutions like Immuta can automate data redaction using attribute-based access control, helping ensure that distributed data is only available to the appropriate users.
After Completing a Project
If you want to ensure that you have all the data needed for a specific task and don’t want to accidentally redact important data before analysis, you can redact sensitive data after those analytics tasks have been completed. This will allow you to do the necessary work, then ensure that continued storage of sensitive data doesn’t leave you exposed to leaks or other security issues.
This is another process that can be effectively managed and automated by a platform such as Immuta. Automating your redaction process in this way will help ensure that no step is skipped and that manual user error doesn’t lead to breaches, leaks, or improper data management practices.
Before Archiving Data
Keeping detailed archives and records is essential not only for helping businesses operate successfully, but also keeping them compliant with certain industry and government regulations. So, how can you safely archive data without exposing it to potential future breaches? By redacting sensitive data just before archiving.
Many businesses now use automated archiving procedures, which can be paired with a data redaction tool that automatically combs through each data set and report to ensure that no sensitive data is left behind before archiving.
Before Disposing of Data
At first thought, removing sensitive data from a document right before deleting it may seem like wasted effort, like cleaning a plate right before throwing it away. But think about the last time you threw away an old credit card or bill. You most likely cut or shredded it before discarding it. That’s because throwing something away doesn’t always mean it can’t be recovered by someone with less-than-good intentions.
With that in mind, taking the dual step of redacting sensitive information before disposing of reports can add a layer of protection in the event that someone is able to recover those deleted reports in the future.
How to Manage Data Redaction
While data redaction is an essential part of data security, it doesn’t have to slow down your data management process. Immuta can be programmed to automatically replace values in reports and other sensitive documents with Redacted or any other constant value, making the data redaction process easy, fast, and seamless.