Tokenization not only increases the security of sensitive data but also reduces the scope of compliance and associated costs. Tokenization’s versatility enables businesses to design customized Tokenization solutions for secure data management to help them match their data utility needs with data security concerns.
This blog looks deeper into data tokenization and how it works. We’ll also look at some typical data tokenization use cases and how they differ from encryption.
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Table of Contents
• The Importance of Tokenization for Enhanced Data Security
• Does Tokenization Mask Data?
• When Should I Use Data Tokenization? Top Tokenization Use Cases
• What’s the Difference Between Tokenization and Encryption?
What Is Data Tokenization?
Tokenization in the era of digital privacy, when data is one of the most valuable assets, is vital for businesses to ensure their data security. Data security and governance are frequently listed as the top problems for data executives, while data leaks and breaches have become more common.
Organizations increasingly depend on data tokenization to resolve data privacy concerns and increase privacy preservation. This technique entails replacing sensitive data, such as a customer’s social security number or bank account number, with a random data string known as a token.
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Tokens have no inherent meaning and cannot be reverse-engineered to disclose their original data. Only the system that generated the token can use a well-known mechanism to obtain the original data it represents.
The Importance of Tokenization for Enhanced Data Security
According to a poll of data experts, 75% of organizations acquire and keep sensitive data that they currently have or plan for implementing data tokenization strategies. Tokenization is a method of securing data by replacing it with tokens that act as surrogates for the underlying information.
For example, a customer’s 16-digit credit card number might be substituted with a random string of numbers, letters, or symbols. This tokenization procedure would make it impossible for a future attacker to exploit the customer’s credit card number, making online payments infinitely more secure.
When businesses depend on tokenization, they may continue to use their data in the same way they always have while simultaneously being protected against the hazards associated with retaining sensitive data.
This makes companies significantly less exposed in the case of a data breach and puts them in a far better position to comply with many ever-changing data compliance laws and regulations.
Data tokenization assists organizations in striking the appropriate balance between realizing the total value of their data and keeping it secure. It is an effective technique for obtaining much-needed information in highly regulated areas such as healthcare and financial services without increasing the surface area for risk.
Simultaneously, employing data tokenization can assist in earning customers’ trust by providing them with the piece of mind that their personally identifiable information (PII) will stay in the right hands.
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What is Detokenization?
Swapping the token for the original data is known as detokenization. Only the original tokenization system is capable of detokenization. There is no other way to get the original number from the token alone.
Tokens can be single-use (low-value) for one-time debit card transactions that do not need to be retained or persistent (high-value) for items like a repeat customer’s credit card number that needs to be stored in a database for repeating transactions.
As previously stated, a token is a bit of data that serves as a substitute for another, more valued piece of information. Tokens have almost no value on their own. They are only helpful because they represent something important, such as a credit card main account number (PAN) or Social Security number (SSN).
Does Tokenization Mask Data?
Data masking desensitizes sensitive data by modifying it so it cannot be linked to the original data. Instead of wiping or replacing data with blank values, it replaces sensitive areas with data disguised to mimic the properties of the original data.
Tokenization is a type of data masking that creates a masked version of the data while also storing the real data in a secure location. This results in masked data tokens that cannot be traced back to the original data but provide access to the original data when necessary.
When Should I Use Data Tokenization? Top Tokenization Use Cases
Data tokenization can help safeguard data in a variety of contexts, in addition to making processes like online payments more secure. These are some examples:
1. PCI DSS Compliance
The Payment Card Industry Data Security Standard (PCI DSS) applies to any organization that takes, processes, stores, or transmits credit card information to ensure data security.
To achieve this standard, data tokenization is utilized because tokens are often not subject to regulatory compliance and data tokenization requirements such as PCI DSS 3.2.1, provided there is adequate separation between the tokenization implementation and the applications that use the tokens. Tokenization saves organizations a significant amount of time and administrative expenses.
2. Third-Party Data Sharing
Sharing tokenized data through tokenization techniques for sensitive data minimizes the dangers of giving third parties access to such information. Tokenization also enables the organizations responsible for that data to avoid any regulatory obligations that may apply when data is exchanged between jurisdictions and settings, such as data localization regulations such as the GDPR.
3. Least Privilege Management Principle
The idea of least privilege ensures that people only have access to the information required to execute a specified activity. Tokenization allows for least-privileged access to sensitive data.
When data is co-mingled in a data lake, data mesh, or another repository, tokenization can ensure that only those individuals with the requisite access can perform the de-tokenization method to access sensitive data.
Tokenization is also useful for allowing sensitive data for other purposes, such as data analysis and minimizing risks identified by a risk assessment process or threat model.
What’s the Difference Between Tokenization and Encryption?
Tokenization and encryption are frequently used interchangeably. Both are data obfuscation techniques that aid in data security in transit and at rest. Despite their similarities, it is critical to recognize the differences between these approaches to data protection through tokenization.
While tokenization substitutes data with a randomly generated token value, encryption uses an encryption method and key to turn plaintext information into a non-readable form known as ciphertext.
The best method for your organization is determined by its needs. Tokenization, for example, is ideal for organizations that want to comply while minimizing their PCI DSS requirements. Encryption is appropriate for transmitting sensitive information to those with an encryption key.
As remote work has grown in popularity in recent years and data is increasingly accessible from various locations, encryption has become a popular technique for protecting against data breaches or leaks.
ATMs frequently employ encryption technology to maintain data security while in transit. This makes it an excellent solution for organizations that must encrypt massive data.
Applying Data Tokenization for Secure Analytics
Tokenization will be critical to maintaining data security and compliance as organizations collect and retain more data for analytics, particularly in an increasingly regulated environment.
However, the speed with which organizations must enable data access and the complexity of today’s cloud systems may make implementation more complicated than it is worth – without the correct tools.
Conclusion
Data tokenization is a powerful technique that enhances data security while allowing organizations to maintain data utility. By replacing sensitive data with tokens, businesses can significantly reduce the risk of data breaches and comply with various data privacy regulations.
Tokenization offers advantages such as secure online payments, PCI DSS compliance, third-party data sharing, and implementing the principle of least privilege management. It differs from encryption by using randomly generated tokens instead of transforming data into ciphertext.
While the benefits of data tokenization are numerous, organizations should carefully consider their specific needs and evaluate the feasibility of implementation. Data tokenization is a valuable tool for protecting sensitive data, maintaining compliance, and gaining customer trust in an increasingly data-driven world.
