CipherTrust Tokenization with Data Masking for PCI DSS 4.x

Reducing PCI DSS 4.x audit scope

For data protection to be valuable, it must support existing workflows and AI-driven workflows, which is increasingly difficult due to massively fragmented data sprawl across hybrid environments, differing user access needs, evolving threats, shadow IT, human error, regulations/laws and AI exposure boundaries. 

Driven by data privacy and sovereignty regulations around the world, the data types that need to be protected are no longer just credit cards, but also include U.S. Social Security numbers, Drivers Licenses, U.K. National Insurance numbers, Passport numbers, National Identity numbers and health information in countries around the world. The need to use sensitive data in advanced technology environments such as cloud and data lakehouses leads to further complications. 

AI runtime and persistent exposure boundaries must be protected when AI is operational in case sensitive data is present. Runtime exposure boundary threats can surface when AI is processing data. Persistent exposure boundary threats can surface where AI stores or propagates data after processing. 

In this white paper, we’ll look at the difference between using Tokenization and Encryption to maintain database schemas for PCI compliance, the role of Dynamic Data Masking (DDM), and how CipherTrust Tokenization solutions leverage the CipherTrust Data Security Platform (CDSP) to support PCI DSS 4.x.