Explain What is Data Obfuscation?

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Data privacy and security have never been a bigger worry than now. It’s not just that the entire world depends on data; data breaches are increasing in number and volume.

The Privacy Rights Clearinghouse’s Chronology of Data Breaches includes over 9,000 data breaches made public in the last five years. It is more than 10 billion data records that were breached.

As per IBM, data breaches are becoming more expensive. Data obfuscation could have prevented the release of many of these documents, even though the breach was successful.

Data obfuscation can be described as a method to hide the significance of data to provide an additional layer of protection for data. If there is a data breach, sensitive data will not be helpful for attackers.

The data of the organization — as well as anyone else that is included in the data will be safe. The organization should be able to prioritize hiding sensitive data in its databases.

Top Data Obfuscation Methods

If you ask 10 people about the meaning of data obfuscation, you’ll receive 12 different responses. There are many other techniques, each designed for specific uses.

Obfuscation is a broad term that describes various methods that alter data into different forms to secure confidential and personal data.

Three popular ways to conceal data include tokenization, encryption, and masking data.

Tokenization, encryption, and data masking function in various ways. Tokenization and encryption can be reversed because the initial values could be obtained from the encrypted data.

Masking data, on the contrary, is unreversible if it is done correctly. Let’s dive into these three kinds of data obfuscation.

Encryption is exceptionally secure. However, it cannot work on or examine the data once encrypted.

The more complicated the encryption method, the better protected the data will be protected from unauthorized access. The encryption method is an excellent obfuscation method to protect sensitive information securely.

Tokenization replaces sensitive data with an insignificant value. The process cannot be reversed. However, it is possible to map your token to the original data.

Tokenized data can support operations such as processing a credit card payment without divulging your credit card’s number. The data has never left the company and cannot be viewed or decrypted by an external processor.

Data masking replaces real but fake data with original data to protect privacy. With masking data testing or training, development or support teams can use a data set without putting accurate data at risk.

Data masking is known by a variety of names. You might have heard it described as scrambling, blinding, or shuffling data.

This process of permanently stripping the personally identifiable details (PII) of sensitive information is called data anonymization or sanitation. Whatever you call it, fake data is replaced by actual data. There is no way to restore the original value of data that has been masked.

Data Masking Vs. Data Obfuscation In Different Forms

Data masking is one of the most popular methods for obfuscating data. The fact that it isn’t reversible makes this masking method extremely secure and cheaper than encryption.

The benefit of masking data is that it allows you to keep the integrity of your data. For example, testers, as well as developers of applications, can make use of datasets that are populated with accurate data. Making use of only actual production data can protect your company from risk.

As a form of opaqueness integrity doesn’t necessarily indicate that the information is correct. Instead, it refers to the fact that the data set maintains its function despite data anonymization.

For instance, a credit card number could be substituted with a different 16-digit number, which will meet the criteria for an actual credit card. If it fails to pass the checksum, it doesn’t have the integrity of data. All field references must be made in order to guarantee security.

In a nutshell, there are two significant differences between data masking methods and obfuscation techniques for data, such as tokenization or encryption.

  1. Data masking is helpful in its obfuscated form.
  2. After masking data and the original values are lost, they cannot be found.

Benefits Of Data Obfuscation

The most obvious and crucial benefit of data obfuscation is the ability to hide sensitive data from people who aren’t permitted access. It also offers benefits beyond data security:

Risk and compliance with regulatory requirements: Privacy regulations, including GDPR, require reducing personal data.

Through the use of data obfuscation you are able to collect and share only the minimum amount of personal information. Obfuscation helps reduce the risk of being fined and protects your data when breached.

Data sharing With the growing importance of data sharing, Data masking is the only way forward. It is possible to share data with other parties or share data publicly if you conceal sensitive information.

Data governance Obfuscation is an essential element of controlling access to data. If you consider it, there are many businesses that do not require unlimited access to data.

If non-production environments don’t need personal data, don’t expose sensitive information. It reveals your business to potential risk. A plan for obfuscation is a must in the data governance strategy

In contrast to static masking, which creates a single masking dataset, dynamic masking provides granular control.

Dynamic data masking allows permissions can be denied or granted at various levels. Users with a business need access to actual information, while others can only access the data they require to be able to see.

Flexibility: Data masking also is highly customizable. You can choose the fields of data that are covered and how exactly to select and format every substitute value. For instance, U.S. Social Security numbers are formatted as NNN-NNN-NNNNN, where N is an integer between 0 and 9.

It is possible to replace the first five numbers with an X-shaped letter. It can be substituted the nine digits with randomly generated numbers.

You can cover any number; it is contingent upon what is the most appropriate for your requirements.

Different techniques for data obfuscation provide various advantages. The most efficient method is dependent on the source of the data as well as the specific purpose for which you intend to use it.

In a health clinic, patients’ health information might need to be temporarily hidden during transport. Research studies may decide to remove PII altogether.

Problems With Data Obfuscation

While data obfuscation does have its advantages, however, it also brings problems. The main challenge to overcome is the planning process, which could take up lots of time and money. Management of data will always be an all-encompassing initiative.

The data owners, stewards, and those who use the data must all be involved in determining strategies for data obfuscation. Making the decision of which data is required to be encrypted may require longer than you think.

If your company is struggling with the health of your data, it is possible that you won’t be aware of the exact location of sensitive data stored.

Let’s examine the challenges of every method of obfuscation:

The encryption can obscure structured and unstructured data but schemas that preserve formats are less secure.

Tokenization can only be used to store structured data fields like security numbers or  credit card. When a database grows in size, the performance and security of tokenization become challenging to increase the size.

Masking data implementation may require significant effort. Data masking’s incredible customizability has one drawback: you’ll have to tailor each field to meet your requirements.

Data Masking And Cloud

All size companies and sectors are embracing cloud-based technologies. Cloud-based services accelerate data delivery and provide more flexibility over on-premises solutions. Although cloud computing has been proven to be as secure and even safer than maintaining data on-premises, a few aren’t entirely secure.

Data obfuscation may help mitigate the risks. If data is encrypted before being loaded into a cloud-native data repository, it would be inaccessible to attackers even if they breach it.

The data stolen would be only false data substituted with data masking. Utilizing a cloud-native service that includes tools for masking data built-in extract, transform, and load (ETL) processes makes it easier to implement.

Data Obfuscation Best Practices

The old carpenter’s apprentice applies to the planning of data obfuscation. Data Obfuscation of successfully is accomplished by following the best techniques. Include these steps into your plan for data obfuscation:

  • Receive support and buy-in from your data owners, the data stewards, and management
  • Find sensitive data by working with departmental data Stewards.
  • Incorporate data privacy policies, regulations, and standards that your company must adhere to
  • Choose the appropriate data masking methods and the rules and formats for every piece of sensitive information. Organizing data into groups with common traits can make this process.
  • Pick a tool to make the process as efficient as it can be

If there is no specific need for the obfuscation technique to be reversible, you should use an irreversible masking approach for data. It is the best way to safeguard sensitive data, and a masked data set is equally valuable for testing purposes.

In order to ensure data masking has been performed correctly, ensure your data integrity is protected. Data integrity is vital, so data masking is as effective as data from the beginning. For instance, you’ll need to prepare for the future analysis of usage by credit cards.

Determining the credit card numbers in your database from each bank is possible. Because the first six digits of a credit card’s number are the bank’s identifier (BIN) which is all you must know. If you misinterpret the other numbers, you’ll have the data you need, but also maintain integrity and safeguard sensitive information.

How Do You Use Data Obfuscation To Your Advantage? 

There are various kinds of data obfuscation, the appropriate method will depend on the particular job. The most frequent use cases are training, testing applications, development of apps, and support. These require data masking – permanent replacement of sensitive data with accurate data.

Masked data will preserve the authenticity of the original dataset. It cannot be decrypted. You can alter it to meet your need.

Masking data can have many advantages regarding governance, risk, and compliance. But, you must know that correctly performing the task can take time and energy.

Implementing best methods can increase the effectiveness of the procedure. The most effective way to reduce expenses and time is, to begin with a well-constructed plan and automate the masking data wherever feasible.

Many methods simplify the process of masking data. These extensive suites of applications concentrate specifically on data integrity. These Data Fabric empowers companies to manage and collect the transformation, exchange, and sharing of healthy data.

Are you ready to decrease your regulatory footprint, gain savings, and lower risk? Distribute quality data across your business without having to reveal sensitive data.

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