Data Masking

Protect Privacy While Maximizing Data Value

Data Discovery Solution

Both static and dynamic data masking are techniques used to protect sensitive data. They transform original data into a sanitized version, ensuring that sensitive information is not exposed to those who shouldn’t have access to it.

Data Masking Capabilities are available with

What Customers Have to Say About PK Protect

“Data privacy is going to continue to be important. And given that we operate at a global scale, we have to stay on top of that. This is why we are making investments in technology and working with partners like PKWARE.”

Harveer Singh, Chief Data Architect & Global Head of Data, Western Union

Data Privacy Inside Western Union - PKWARE

Data Masking empowers organizations to easily enforce complex data access policies that limit the exposure of sensitive data while ensuring mission critical applications that require access to actual production data operate as designed with no impact to the end user. Sensitive data is masked in real time as it is accessed based on user roles and policies, leaving the original information at rest on the database untouched.

Data Masking Benefits for Your Data Security Posture

Static Data Masking

  • Permanent Anonymization: Once the data is masked, the original data is irretrievable. This makes it secure for scenarios where the original data isn’t required, such as in test environments.
  • Consistency: Because the data is permanently transformed, the masked values remain consistent across all databases and datasets. This helps in maintaining referential integrity.
  • Reduces Data Breach Risk: If the static masked data is exposed or stolen, there is minimal risk since the actual sensitive data isn’t revealed.
  • Ideal for Non-Production Environments: Developers and testers can work with realistic, but non-sensitive data. This means they can test software or analyze data without risking exposure of the real data.
  • Regulatory Compliance: Helps organizations adhere to data protection regulations that demand data privacy in non-production environments.

Dynamic Data Masking

  • Masking Data in Motion: The original data remains unchanged in the database. Masking is done in real-time, during the query execution phase. Users receive the masked data based on their permissions.
  • Flexibility: Since the masking is done in real-time, it can be easily adjusted as requirements or user roles change without affecting the actual stored data.
  • Minimal Overhead: There’s no need for a separate masked database for different users or purposes. This can result in savings on storage and administration.
  • Real-Time Data Access: Users can work with up-to-date data, making it suitable for situations where accessing the latest data is critical, but revealing sensitive information is not necessary.
  • Role-Based Access: Different users can see different views of the same data based on their role and permissions. For instance, a customer service representative might see only the last four digits of a customer’s credit card number, while a financial officer might see the entire number.

Both static and dynamic data masking have their place in every enterprise organization’s data security posture management strategy. The choice between them often depends on the specific use case and requirements. For example, static data masking might be more suitable for creating secure test environments, while dynamic data masking might be ideal for real-time data access with role-based restrictions.

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