Dynamic Data Masking for SAP HANA

Introduction

In today’s data-driven world, protecting sensitive information is more crucial than ever. Organizations handling vast amounts of data must ensure its security while maintaining functionality. Dynamic data masking for SAP HANA offers a powerful solution to this challenge.

Did you know that the average cost of a data breach reached $4.35 million in 2022? This staggering figure underscores the importance of robust data protection measures.

Let’s see how dynamic data masking in SAP HANA can improve data security, meet regulations, and keep customer trust.

What is Dynamic Data Masking?

Dynamic data masking (DDM) is a security feature that conceals sensitive data in real-time. It displays masked information to unauthorized users while allowing authorized personnel to view the original data. This technique helps organizations protect confidential information and meet various regulatory requirements.

SAP HANA’s Native Data Masking Capabilities

SAP HANA provides built-in features for data masking and query redaction. These tools offer a first line of defense in protecting sensitive information directly within the database.

View-Based Masking

SAP HANA uses view-based masking to implement data protection. Here’s a simple example:

CREATE VIEW MASKED_CUSTOMERS AS
SELECT 
    CUSTOMER_ID,
    CASE WHEN USER = 'ADMIN' THEN FULL_NAME
         ELSE SUBSTRING(FULL_NAME, 1, 1) || '****'
    END AS MASKED_NAME,
    CASE WHEN USER = 'ADMIN' THEN EMAIL
         ELSE SUBSTRING(EMAIL, 1, 2) || '****@example.com'
    END AS MASKED_EMAIL
FROM CUSTOMERS;

This view masks full names and email addresses for non-admin users.

Query Redaction

SAP HANA also supports query redaction to prevent sensitive data from appearing in logs. For instance:

CREATE FUNCTION REDACT_SSN(ssn VARCHAR(11))
RETURNS VARCHAR(11)
AS BEGIN
    RETURN CASE WHEN USER = 'ADMIN' THEN ssn
                ELSE '***-**-' || RIGHT(ssn, 4)
           END;
END;

This function redacts Social Security Numbers in query results for non-admin users.

Dynamic Data Masking for SAP HANA with DataSunrise

While SAP HANA’s native capabilities are useful, DataSunrise offers more advanced and flexible dynamic data masking solutions.

Creating a DataSunrise Instance

To set up DataSunrise for SAP HANA masking:

1. Create your SAP HANA instance in DataSunrise:
2. Configure masking rules based on user roles and data sensitivity.

Implementing Dynamic Masking

With DataSunrise, you can:

• Create granular masking rules for different users and roles.





• Apply various masking techniques (e.g., substitution, shuffling, encryption).
• Mask data in real-time without modifying the original database.

User Experience

Let’s see how dynamic masking works in practice:

SELECT * FROM TESTROWS t ;

This approach ensures that it protects sensitive data while maintaining functionality for authorized users.

Benefits of Dynamic Data Masking for SAP HANA

Implementing dynamic data masking for SAP HANA offers several advantages:

1. Enhanced data security
2. Simplified compliance with regulations
3. Reduced risk of data breaches
4. Maintained data usability for authorized users
5. Flexible and customizable protection

Masking Types and Techniques

Different types of data require different masking approaches. Here are some common techniques:

1. Substitution: Replace sensitive data with realistic but fake values.
2. Shuffling: Rearrange data within a column.
3. Encryption: Transform data using cryptographic algorithms.
4. Nulling: Replace sensitive data with null values.
5. Redaction: Replace part or all the data with asterisks or other characters.

Achieving Regulatory Compliance

Dynamic data masking plays a crucial role in meeting various regulatory requirements:

• GDPR: Protect personal data of EU citizens
• HIPAA: Safeguard healthcare information
• PCI DSS: Secure payment card data

By implementing robust masking strategies, organizations can demonstrate their commitment to data protection and avoid hefty fines.

Best Practices for Dynamic Data Masking

To maximize the effectiveness of your data masking strategy:

1. Identify sensitive data through regular audits.
2. Implement least privilege access principles.
3. Regularly review and update masking rules.
4. Combine masking with other security measures (encryption, access controls).
5. Train employees on data security best practices.

Challenges and Considerations

While dynamic data masking is powerful, be aware of potential challenges:

• Performance impact on query execution
• Complexity in managing masking rules
• Ensuring consistency across different environments
• Balancing security with data utility

Address these challenges through careful planning and regular optimization of your masking strategy.

Future Trends in Data Masking

As data protection evolves, expect to see:

• AI-driven masking techniques
• Integration with cloud-native services
• Enhanced automation in rule creation and management
• Improved performance optimization

Stay informed about these trends to keep your data protection strategy current and effective.

Conclusion

Dynamic data masking for SAP HANA is a crucial tool for protecting sensitive information and ensuring regulatory compliance. By implementing robust masking strategies, organizations can significantly reduce the risk of data breaches and maintain customer trust.

Having a strategy for data protection is crucial. This plan can involve using SAP HANA or tools like DataSunrise for protection. Having a thorough plan is crucial for ensuring the security of data.

Remember, data protection is an ongoing process. Regularly review and update your masking strategies to stay ahead of evolving threats and compliance requirements.

DataSunrise offers user-friendly and flexible tools for database security, including audit, masking, and data discovery features. Contact our team for an online demo and explore how you can enhance your SAP HANA data protection strategy.