Data Masking

In this article:

• Introduction

• Why is Data Masking Important?

• How DvSum Implements Data Masking

  • Masking Columns

Introduction

Data masking is a security technique that obscures sensitive information by replacing it with fictional but realistic data. It helps protect personally identifiable information (PII) while maintaining data usability for testing and analytics. DvSum provides data masking through the use of tags, ensuring data privacy and compliance. This article explains different masking techniques, their importance, and how to configure them in DvSum.

Why is Data Masking Important?

Data masking is essential for:

• Compliance: Meets regulatory requirements like GDPR, HIPAA, and PCI-DSS.
• Security: Protects sensitive information from unauthorized access.
• Risk Mitigation: Reduces the risk of data breaches and leaks.

How DvSum Implements Data Masking

Masking Columns

Data masking in the DvSum application serves as a privacy shield, obscuring sensitive information with masked placeholders, such as "XXX". From the "Field Dictionary", data security admins can mask the column using More Actions - Data Classification:

Internal/ Public: By selecting internal / public, Column classification will be set as Default

Sensitive: By selecting Sensitive, Column Data will be masked as "XXX " all across the application.

Restricted: By selecting Restricted, the Column will be marked as a Hidden Column and will be masked as "XXX " all across the application.

When the column is marked as sensitive, an icon will be shown with the column name and the Data for the sensitive column will be masked as "XXX" all across the application.

When the rule is executed on the table that has a masked column, the exported Excel file will show masked Data for the sensitive Column.