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News

Sensitive Data Protection through Tokenisation

NuBridges : 22 June, 2010  (New Product)
Protect Token Manager from nuBridges for multiple data centre assists in complying with privacy laws internationally
nuBridges has announced Token Manager Release 2.0. The newest version of nuBridges' Format Preserving Tokenization solution includes support for a new architectural model, coordinated tokenization by multiple data centres simultaneously, and even greater protection and configuration flexibility for personally identifiable information (PII) and protected health information (PHI), helping enterprises comply with US and international privacy laws.

"Integrated encryption and tokenization solutions have proven their value in protecting cardholder data and reducing PCI compliance exposure," said John Pescatore, Gartner Vice President and Research Fellow. "By extending these capabilities to secure other types of sensitive data, enterprises can make major steps forward in protecting the business against targeted attacks."

"Since we introduced our tokenization solution in April 2009, we've been intent to provide the best and most comprehensive data security solution in the market, and also to ensure that it meets our customers' needs for flexibility and non-invasiveness across multiple use cases and environments," said Gary Palgon, nuBridges Vice President of Product Management. "nuBridges Protect Token Manager 2.0 builds upon our 'always protected' vision to allow our customers to protect sensitive data wherever it originates, travels or is stored, and to stay ahead of industry data security mandates and privacy laws."

nuBridges Protect now offers the ability for sensitive data to be encrypted at the point of capture (for example Payment Entry Device or Point of Sale system), then securely transmitted to the centralized Token Manager that, in turn, tokenizes the data so that a highly configurable, meaningless token can be used in all downstream systems. This eliminates the risk of data exposure during transit from point of capture to the Token Manager. It also supports a "store and forward" approach at encryption endpoints that is ideal for scenarios where endpoints are vulnerable to network disruption, such as remote retail operations.

Token Manager 2.0 also enables tokens to be generated in multiple data centre locations simultaneously. Many extended enterprises have several operational and disaster-recovery data centers that need to generate and share tokens. This new capability of Token Manager 2.0 provides:

* Scalability: Serving tokens from multiple data centres assures performance and reliability for geographically-dispersed, high-volume operations.
* Disaster Recovery/High Availability: In the event a primary data centre becomes unavailable, a disaster recover site can be instantly brought into service without the risk of a token collision.
* Centralized Key Management: The ability to centrally administer keys and other security functions is preserved.

For some use cases, it is important to maintain referential integrity across all tokens - assuring that a unique data value such as a credit card number or national ID number will always have the same token value. This allows enterprises to run reports and analytics on tokens without having to expose the underlying sensitive data to unauthorized users. Referential integrity is typically important to organizations that are using tokenization as part of their Payment Card Data Security Standard (PCI DSS) compliance strategy. Referential integrity has always been a feature of nuBridges Protect Token Manager.

As use of nuBridges Protect Token Manager expands to other use cases, however, it is sometimes desirable to break that one-to-one relationship. Token Manager 2.0 provides enterprises with the ability to "turn off" referential integrity and/or format preservation, and configure the tokenization in a variety of ways. This is ideal for non-unique PII such as date of birth, salaries, and zip and postal codes, patterns of which can potentially reveal private information about individuals or groups. A simple example of this is salary information, where if two employees earn the same salary and therefore have the same token, having knowledge of one person's salary (and token) would expose the other person's salary. Breaking referential integrity is needed to preserve the privacy of both employees.
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