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Data Redaction: Meaning, Types, and Prevention

  • Sangita Kalita
  • Sep 07, 2022
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“Privacy is not something that I’m merely entitled to, it’s an absolute prerequisite.” 

– Marlon Brando

 

Nobody disputes the importance of data. Every organization, whether it be a little firm or a major corporation, needs data to track its performance, examine the market, find vulnerabilities or flaws, and decide about how to grow or enhance its operations.
 

Data managers and security specialists are up all night worrying about how to keep this data secure because it comes with a huge amount of responsibility. There are many business models that require the storage and processing of sensitive information, especially personally identifiable information (PII). 

 

Information that can be used to directly or indirectly identify a person is referred to here. Redacting data is one of the finest ways to do this because it is one of the most efficient data security techniques. You might merely need it to protect your business from a data breach, which could damage your reputation. In this blog, you will learn more about Data Redaction.

 

Also Read | Steps for Data Analysis 


 

What is Data Redaction?

 

Protecting sensitive data from hacking or leaks involves the use of data redaction. In an effort to prevent it from being revealed as a whole and used for malevolent or evil reasons, it entails the removal of certain data items from the entire data set.

 

In movies or sensitive documents where certain material has been blacked out, you may have heard the phrase "redacted information." In the process of data redaction, the same theory is used.

 

Basically, this technique divides data into several pieces of information and removes or hides parts that can be used to identify or relate to a certain person, business, or organization. 

 

The first names of all cardholders, or the first and last four digits of their card numbers, could be redacted, for example, if you have the credit card information for your clients saved in your database.

 

In order to conceal and safeguard their sensitive data, businesses all around the world employ data redaction solutions. It not only aids in maintaining the data's security but also protects its validity and integrity. Data redaction can be done using either a static or dynamic approach.

 

Static redaction involves copying or moving the material to a copy where redaction procedures and algorithms have already been applied. It can be applied to big data sets to redact sensitive information. It takes a significant amount of time and resources to accomplish this.

 

Data-in-transit redaction is another name for dynamic data redaction, which involves removing private information from data in real-time. With this method, redacting the data doesn't require batch processing. The drawbacks include large performance overheads and the fact that it is considerably better suited for read-only applications.

 

Also Read | What is Attack Surface Management?

 

Importance of Data Redaction

 

The typical business handles a variety of data types, such as company, customer, and staff data. The requirement for protection against leaks, breaches, and unauthorized access is quite evident for each of these forms of data. 

 

Customer data breaches can have a negative impact on your business' reputation, incur fines from the authorities, and, of course, violate your ethical obligations by endangering your clients. 

 

Employee data leaks can result in many of the same problems, whereas corporate data leaks can reveal confidential information that should be kept private as well as give your competitors useful insights.

 

Limiting authorized access to data — that is, deciding who is permitted to view particular data points — is among the most efficient strategies to prevent illegal access to data. At its core, data redaction is merely one type of access control. 

 

You can limit the sharing of identifying information and other sensitive data by redacting unneeded material before it is viewed or used by a party, reducing the risk of leaks and breaches across your company.


 

Data Redaction vs Data Masking

 

Reading about data redaction will also introduce you to the concept of data masking. Although each of them are tools for data security, there are some fundamental differences between them.

 

In contrast to data redaction, which involves replacing specific sensitive information with less sensitive information that has the same structure, data masking involves replacing sensitive information with less sensitive information.

 

Data masking is typically used to generate sample data for testing or training reasons, preventing any personally identifiable information or sensitive data from being exposed or modified during the production or testing phase in an organisation. Additionally, the data types and data structure are preserved with this method, allowing for the use of the data in applications.

 

On the other hand, data redaction is used to hide personally identifiable information or information that is classified from understandable data, preventing any sensitive data from being exposed to the public.

 

It is acceptable to argue that data masking is a technique for "replacing" data with something that has a similar format whereas data redaction is a way to "delete" data. Data masking is frequently thought of as a subtype of data redaction.

 

Also Read | What is Data Validation?
 

 

Can Redacted Data be Restored?

 

Redacting sensitive information essentially removes that particular piece of information in order to preserve data security. Naturally, this would lead you to wonder if censored data could be recovered.

 

Prior to PDF conversion, people would overlay a black box over sensitive information in Microsoft Word documents. The downside of this was that it allowed anyone with access to the Word file to open the black box and see the data hidden inside.

 

Information that has been redacted cannot be retrieved in more recent versions of PDF readers and even Word, making them significantly more secure than earlier versions.

 

In essence, you can only recover redacted data if you have a copy of the original file on hand or if you have access to highly qualified data engineers who can access the metadata and perform the task on your behalf.

 

Material redaction is therefore a very helpful and effective approach for securing sensitive data, but it also necessitates that you retain your original data securely to prevent access.

 

Also Read | What is Data Processing and Why is it Important?


 

Benefits of Data Redaction

 

You are already familiar with how data redaction operates and how it may be used to keep private information from the public as well as those with bad intentions. Let's have a look at a few advantages of data reduction:

 

  1. It Makes Data Usable

 

You must use data for your business operations regardless of the industry you work in. In some circumstances, you must also make the data publically accessible. 

 

Applying a data redaction strategy will allow you to desensitize the data, making it usable without sacrificing security. That is true, of course, unless the data has been redacted and you need the redacted data instead; in that case, you should select another anonymization method.

 

  1. It Ensures Compliance

 

Due to the rise in data breaches encountered by businesses worldwide over the past ten years, several data privacy and security policies have been put in place. Companies can adhere to these rules by using data redaction techniques.

 

  1. It Helps Keep Data Secure

 

Redaction of sensitive or important data also aids in maintaining the integrity and security of that data. Data breaches have significantly increased over the past few years, as you may already be aware, and they have a negative impact on organizations reputations. These problems are avoidable by data redaction.

 

Also Read | Guide to Data Profiling


 

Data Redaction Use Cases

 

Your firm, industry, data kinds, and data management strategy will determine when you need to concentrate on data redaction. To ensure the safety of your company, its workers, and its clients, there are some general handoff points and events that could benefit from data redaction. 

 

Here are the top five use cases for data redaction that your company can benefit from, along with information on how to approach each one specifically.

 


The image shows Data Redaction use cases which includes when acquiring Data, Before Distributing Data, After Completing a Project, Before Archiving Data and Before Disposing of Data

Data Redaction use cases


 

  1. When Acquiring Data

 

One of the ideal times to redact data is right away after receiving it, before it may be shared with further sources and raise the risk of leaks. Consider quickly redacting any information from a data set that isn't specifically pertinent to the job you or your team will be using it for.

 

Certain data points can be automatically censored using the correct data management technology to speed up your workflow. After that, individual cases of other data might be individually redacted.

 

Before sharing the report or data set with the rest of your team or business, a data security professional at your company can examine your redacted outputs for an additional layer of security to make sure that any sensitive, non-essential data has been redacted.

 

  1. Before Distributing Data

 

You can safely redact any information in your reports that isn't relevant to your organization's operations as soon as you receive it. What about information that might be pertinent to some persons or groups inside your organization but not to others?

 

You should redact sensitive data before it is given to the ‌stakeholders, as opposed to doing so when the information is first acquired. You might redact some engineering data before giving it to a certain team if, for instance, the financial division of your company doesn't need to know about it. 

 

In order to ensure that distributed data is only accessible to the right persons, data access control solutions can automate data redaction using attribute-based access control.

 

  1. After Completing a Project

 

You can redact sensitive data after those analytics jobs have been finished if you want to make sure you have all the data you need for a particular task and don't want to mistakenly remove crucial data before analysis. 

 

Having done the ‌work, you may then make sure that continuing to store sensitive data won't expose you to leaks or other security risks.

 

A platform can efficiently manage and automate this process as well. By automating your redaction procedure in this way, you can prevent any steps from being missed and breaches, leaks, or poor data management practices from being caused by manual user mistakes.

 

  1. Before Archiving Data
     

Keeping thorough archives and records is crucial for a business's smooth operation as well as for ensuring that it complies with all applicable laws and regulations. So, how can data be safely archived without putting it at risk of future breaches? redacting private information shortly before archiving.

 

In order to make sure that no sensitive information is left behind before being archived, many firms now employ automated archiving processes that can be used in conjunction with a data redaction solution.

 

  1. Before Disposing of Data

 

At first, glance, deleting a document before removing critical information from it may seem like a waste of time, similar to washing a plate before tossing it away. But recall the last time you disposed of a credit card or old bill. 

 

Before throwing it out, you most likely cut or shredded it. This is due to the fact that simply throwing something away doesn't guarantee that someone with ill motives can't recover it.

 

In light of this, removing critical information from reports before discarding them can give an extra layer of security in the event that someone manages to retrieve those deleted reports in the future.

 

Also Read | Data Visualization Techniques

 

Redaction of data is frequently thought of as the initial stage when developing a data privacy plan. You might be able to utilise it to protect the private information held by your company and to reduce the possibility of data leaks or breaches.

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