Data Tokenization Tools.

Eliminate the risk of a mass data breach with a patented
approach to operational and bulk data tokenization. 

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Advantages of entity-based
data tokenization tools

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Tokenize for one,
or for all

Tokenize individual data in real-time operational use cases; or process large volumes via batch processing.

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mass breaches

Safeguard data at the business entity level, with individual "micro-vaults" (patented technology).

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Comply with privacy and security laws

Assure GDPR / CCPA / PCI DSS compliance, by adapting to changes on the fly.

Multi-vault data tokenization tools

K2View Tokenization_Diagram
K2View Tokenization_Diagram

Real-time tokenization tools, based on a business entity approach, provide the most secure, operationally efficient, and scalable solution for data tokenization. They deliver a central mechanism for tokenizing and detokenizing data, for both operational and analytical workloads.

Entity-based data tokenization tools uniquely store sensitive data, and corresponding tokens, for each business entity (say, customer) in its own Micro-Database™. Each Micro-Database functions as a "micro-vault" for each customer, individually encrypted with its own 256-bit encryption key.

So, instead of an enterprise having to maintain a single, centralized “mega-vault” for 10 million customers, Entity-based data tokenization tools manage 10 million micro-vaults, one for each customer. This is data security at its most granular level.

With real-time data tokenization tools, enterprises benefit from:

  • Unmatched protection of sensitive data
  • Reduced cost in retrofitting existing systems to meet data security standards
  • Full compliance with customer data privacy regulations
  • Assured relational integrity with regard to all tokenized data
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Data protection – from inside, out

Data tokenization tools are especially relevant today, because the majority of
data breaches are caused by insiders, whether accidentally or intentionally.
Recent reports confirm that:

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of all CEOs feel vulnerable to insider threats, and confirm greater frequency of attacks.
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think that privileged IT users pose the biggest insider security risk to organizations.
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believe that detecting insider attacks has become more difficult, after migrating to the cloud.

Encryption, tokenization,
or masking?


Encryption alters sensitive data mathematically, however the original pattern remains within the new code, meaning that it can be decrypted. The ability to reverse encrypted data is its Achilles Heel. Although complex algorithms do a great job encrypting sensitive data, ultimately all encrypted data can be reversed, and revealed.

Tokenization is designed to be reversible. Data tokenization is the process of substituting sensitive data with random, meaningless placeholders, instead of relying on algorithms, which can ultimately be hacked. If an application or user needs the original, real data value, the algorithm is reversible under certain security conditions and credentials. Data tokenization tools securely store the mapping to the original data separately, so even if hackers manage to get to your tokens, your sensitive data is not compromised.

Data anonymization, or masking, is one-way and not reversible. Entity-based data tokenization tools can be combined with data masking tools whereby sensitive data (such as names, Social Security Numbers,  or dates of birth) is replaced with synthetic, format-preserving valid data.

Entity-based data tokenization
tools capabilities

With real-time data tokenization tools, you can:

Continually ingested data


  • Continually ingest clean, up-to-date data, from multiple source systems.

  • Identify, unify, and transform data into individual Micro-Databases.

  • Ensure micro-DB data freshness, without impacting underlying systems.

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  • Have it your way, by tokenizing for a specific data product (business entity), for a specific transaction; or in batch, for bulk workloads.

  • Protect each and every micro-DB, with its own encryption key and access controls.

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  • Optimize tokenization for operational and analytical systems.

  • Use our APIs for tokenization and detokenization.

  • Assure ACID compliance for token management.

  • Tokenize in milliseconds, no matter how tables are being joined.

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Better compliance
through tokenization

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Together with data masking, data tokenization tools enables enterprises to comply with increasingly stringent compliance laws, such as the Payment Card Industry Data Security Standard (PCI DSS).

Any business that accepts, transmits, or stores credit card data is required to be PCI DSS-compliant, to protect against fraud and data breaches. Non-compliance could lead to severe penalties and fines, as well as brand damage.

The combination of tokenization tools and data masking tools supports PCI DSS compliance by reducing the amount of PAN (Primary Account Number) data stored in an enterprise’s databases. With a reduced data footprint, enterprises have fewer requirements to contend with, reducing compliance risk, and speeding up audits.

Get the complete handbook on data tokenization

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data tokenization tools.

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