What is Data Tokenization & Data De-Tokenization?
Tokenization is a specific technique of bartering critical data with non-critical data. This non-sensitive data, known as a token, has no explainable value, is only an identifier that connects back to the sensitive information, and thus makes access to information impossible for a user.
The major aim of tokenization is to save the original data from getting exposed and also protect its value. The process of tokenization is completely different from encryption, where the susceptible data is changed and saved and in any case, it does not allow its use for organizational purposes.
Data Tokenization assists in encrypting the data and thus keeping it safe. For instance, a customer uses his credit or debit card and intends to buy something online. This ‘thing’ can be a product or a service offered by a company. Here, even the managerial level person cannot get the credit card information, as it is available in encrypted codes. In addition to it, no connection between real-time information and encrypted information exists.
Understanding De-tokenization
It is just the opposite of the term called tokenization. It needs the original system where the tokenization occurred, as it is impossible to gain the exact number or token on any other desktop or system. If a one-time online transaction is to be performed then there is no need to store the data for future transactions. On the contrary, if the transaction is to be done many times then encryption must be done so that no human can access the information.
Comparing Tokenization with Encryption
Tokenization vs EncryptionÂ
Encryption changes the mode of the whole information, so changing it back will be a herculean task but this can also be done when it is required. It is true that it is a daunting task but not impossible. Algorithms that are simple to understand can never make encryption possible, thus complex ones are required.
When we say that encryption can be reversed there, one truth is that tokenization can never be overturned. In this case, even if the hackers try to invade the information they can never gain access to the information. This information is not in the form of algorithms, it converts the data into meaningless placeholders which can never be changed back.
If we have to highlight some of the differences between tokenization and encryption then we have the following points to be marked:-
- Tokenization transforms data into some random code and is impossible to reverse whereas encryption can be reversed by the experts.
- Card numbers, security numbers, etc. are instances of tokenization on the other hand files and emails are encrypted.
- Payments over the phone or the transactions, which are made in person, are examples of encrypted data and if we see the use cases of tokenization then they are card on file payments, recurring payments, and storing customer data in varied places.
- Security data in tokenization remains in the locks and encryption, the critical data comes out into the encrypted algorithms. For high security, data tokenization is best but if any chance of the possibility of decrypting might arise then encryption can be used and it is to be mentioned here that even encryption breaking is not a cakewalk.
PCI scope for entrepreneurs can reduce PCI PA DSS scope for business. If we talk about a common element then both eradicate PCI PA DSS scope for vendors.
The data in the case of Tokenization can be easily used and saved in the ‘token vault’ and encrypted, which is locked and can be decrypted when it is necessary. In case of ease of guessing actual value, tokenization can be a bad choice, that is why it is necessary that expert knowledge of using both kinds of methods is necessary. So that a prudent decision can be taken easily.
Market Size, Growth and Trends
Statistics on Tokenization
| Stat | Value |
|---|---|
| Current Market Size (2022) | $2.5 Billion |
| Market size in 2026 (expected) | $5.6 Billion |
| Average cost of a data breach | $4.24 Million |
| Annual Growth rate | 19% |
| Market size in 2030 (expected) | $9.2 Billion+ |
As per the Markets & Markets report, the global market has surged from USD 2.3 billion 2021 to USD 5.6 billion by 2026, at a CAGR of 19%.
There are a few factors that will enhance the effect and spread of tokenization at a rampant rate, which are as follows:
Factor 1: The Rise of Cost-Effective Cloud
Cloud-based tokenization is the method of exchanging sensitive data for an irreversible, non-sensitive placeholder called a token and securely storing the original, sensitive data outside of the organization’s internal systems.
It can be more affordable and easier to integrate than traditional on-premises tokenization. It also further reduces an organization’s risk and compliance scope by removing sensitive data from its data environments.
Additionally, businesses can protect that data without sacrificing its utility or the agility of current business processes by using format- and/or length-preserving tokens as placeholders for the original, sensitive data.
Factor 2: The Rise of Contactless Payments
The key factor is the need for contactless payments these days. Due to Covid-19, people want to exchange liquid money rather than currency.
The method also removes the requirement of an actual storage procedure. There is no need to save credit card and debit card information, and this liquid money can help a lot.
There is a need to have contactless payment to save humanity from the spread of the pandemics like Covid-19.
Factor 3: The Rise in Data Breach
Criminals target businesses that accept credit and debit cards because there is a wealth of intelligence in payment information. Tokenization helps protect businesses from the negative financial impacts of data theft. Even in the case of a breach, valuable personal data simply is not there to steal.
Credit card tokenization helps online businesses improve their data security, from the point of data capture to storage as it eliminates the actual storage of credit card numbers in the POS machines and internal systems.
Fraudulent activities and data breaches are attracting the heed of every organization. The risk of exposing the data to a hacker is inclining day by day and thus needs a check by adopting the apt method of preventing data. Increasing the risk of a data breach can boost the Tokenisation market.
A recent report by IBM found the average cost of a data breach rose 10% over the same timeframe, from $3.86 million to $4.24 million. Interestingly, remote working, and digital transformation due to the pandemic, increased the total cost of a data breach by an average of $1.07 million.
Implement Tokenization Using Data Products
Previously, the data tokenization solutions were storing business partner data in a centralized database. Such a common point of failure was a huge risk. As already discussed at length, web 3.0, the era of decentralized data storage assures greater scope for a data product plan that distributes encrypted and tokenized data sets into millions of Micro-databases. K2View, a leading data management fabric has successfully implemented the approach. The fabric dedicates one micro-database for every business partner thereby reducing the risk of breach while also ensuring compliance.
Moreover, the K2View data product tokenizes the data in real-time for multiple operational use cases. This also works for analytical workloads in batches. Not to miss, they preserve the formats and also retain the integrity of data throughout the data landscape.real-time
Use cases and limitations
4 Data Tokenization Use Cases
As discussed above, tokenization can’t be reversed to its original form outside the tokenization system. This ensures end-to-end protection of the data confidentiality and thus drives multiple use cases across processes. The most common use case is the payment tokenization that is driving digital asset transactions for various applications of web 3.0 such as those related to blockchain. Others include:
1) Tokenization of Historical Data
In many companies, data is stored, which is of no use but can be misused. Historical data like last names, credit card information, and values related to personal health care, etc., so if the analysis is to be done then it can be done without this kind of information too. The algorithms can be used to represent the particular data, which is the easiest and safest way.
2) Tokenization in Development and QA Environments
Tokenization is a method that offers software developers and testers the information they need for data format and continuity. And interestingly, the actual data is not exposed as it is provided in hidden form.
Real values are never visible as they are substituted with tokens before being transferred to the system, and the associations are maintained well. Whereas in encryption the dimensions of the data are maintained as it is.
By this kind of software development and QA data, you eradicate the risk of damage from these systems, and eradicates doubt of data loss and QA teams in the occurrence of loss of data.
Tokenization can assist in consistent data for analysing the growth and QA environments. The risk is of revealing the customer-related data because companies cannot show the actual values. The IT department can develop a way to show the data symbolically to maintain the secrecy.
3) Tokenization for BI
Business intelligence and query, that is BI is an important place where tokenisation is used at a large level. IT departments provide some hidden reports and create them for the user’s benefit, based on which the user can analyze the ongoing trends, and if they are given in plain forms, the responsibility and the task laid can be increased thus making IT department more responsible, it is just that the data must not be directly exposed only relevant information is to be obtained.
Overall, the benefits of tokenization are uncountable and are to be used prudently and widely in several organizations to save the privacy of the users, who reveal trust in the business organization, and no doubt the future is green for tokenization.
4) Simplify compliance of data warehouses and lakes
In the traditional approach, centralized data vaults such as the warehouses and the lakes, receive and store data from multiple sources which could be in structured as well as unstructured formats. This made it complicated to implement data protection as per the regulatory compliance norms. Tokenization resolves this. It enables you keep the original PII separate from the lakes & warehouses. This helps in reducing the risk of infringing any compliance guidelines.
Data Tokenization Limitations
As a security protocol, it complicates the data management infrastructure. Moreover, it is still only supported by a limited number of payment processors, so you may have to go with a payment processing tool that may not be your first choice.
Using the tokenized data requires it to be detokenized and retrieved from a remote service. This introduces a small increase in transaction time to the process which is negligible in most situations.
Moreover, adopting tokenization does not mean that the risk is completely absent from the payment gateway, especially when third-party access to the information is necessary.
In this case, the organization must monitor that the third party has a completely secure system at their end. Using the tokenized information requires it to be de-tokenized and recovered from distant service. Transaction time is delayed and creates a problem.
In a nutshell, it may not,
- May not address all data in use by larger organizations;
- May not work with applications and processing technologies.
So, you have to weigh your choices and collaborate with the right data product platform. By this time, you should build clarity around the key gaps to fill in the data landscape.
Top Tokenization Platforms
Top Data Tokenization Product CompaniesÂ
Given the rapid rise in demand for advanced data tokenization, there’s been a significant increase in the services providers. Apart from premium IT giants such as IBM, we found the following 3 companies that are adding value through their innovative approach. Each one of them is filling the gaps in the existing data architectures. Here’s more.
K2VIEW Best Value
TokenEX Most Detailed
Imperva Best Price
1) K2View
K2VIEW is popular for its unique approach to data fabric and tokenization architecture. For the first time, a fabric has successfully implemented the concept of micro-DB. Here, the infrastructure stores business partner data in a small database. Each one of these micro-databases hold data for a specific business partner only while the fabric maintains millions of them.
The data management product offers a wide range of other services such as mesh, data orchestration, integration and others. The company follows a data-product approach, offering the most secure, scalable, and operationally efficient data tokenization solutions. The system works on a central mechanism for tokenization and de-tokenization of both operational and analytic workloads.
2) TokenEx
ToeknEX offers enterprise grade tokenization services to customers and provides unlimited digital flexibility in the way they access, store and secure data. Their team works seamless with various data processing channels and the latest technologies to help you with asset tokenization services. It is committed to standardize tokenization as a means of regulatory and industry compliance. They are popular for serving the BFSI sector, especially products that work on payment gateway/integration modules.
3) Imperva
Imperva is a data management-consulting firm that provides a range of products/servicescloud systems for encryption techniques for masking the original data. The company’s tokenization services have a razor-sharp focus on end-to-end data security across on-premise systems, cloud systems or a hybrid landscape. Imperva is renowned for its cyber security services and enables the organizations to have a transparent view of their data accessed, held, employed and transmitted through the verticals.
Learn more about Tokenization
Key References and Conclusion
Learn more about Tokenization from the below links:-
A very good article to explain the concept to beginners. The use of lay-man references makes it a good pick for those who have just started with the subject.
Data professionals who have a fair understanding of the landscape should read this comprehensive article on the future of tokenization, the role mesh and the comparison.
The report synopsis provides a quick run-through of the tokenization of industry trends, key sectors, fastest adopters, expected market value and more.
Rewire Your Data Strategy
In this post, we discussed the concept of data tokenization & de-tokenization and how they are an important security components. Next, we learned about the key trends in the market, and the factors driving their adoption including the rise of the cloud in post-COVID times. Finally, we mentioned popular data management products.
From the above discussion, it is clear that digital products regardless of their capital, industry and target reach will have to re-built their data landscape. It should operate in compliance with the demands of web 3.0 and thus prioritise user convenience and confidentiality.
Where do you need tokenization? Share your thoughts.
style=”display:none;”>
Good
test
test
like it like it like it like it
Thanks for submitting your comment!