Dealing with sensitive data in azure

Question

I am ingesting data RaaS and APIs for other source systems, which must be accessed through API and HTTPS or HTTP. ADF does not encrypt the data, and data masking using a dataflow for huge amounts of data is hard. We are dealing with a lot of sensitive data that needs to be anonymized, masked, and encrypted. In this context, what options are available for this scenario? As mentioned earlier, there are sensitive data and compliance aspects of whether third-party tools can be considered if they are available. Please help.

Answer 1

@azure_learner - Thanks for the question and using MS Q&A platform.

When dealing with sensitive data in Azure Data Factory (ADF), especially when ingesting data through APIs and other sources, it’s crucial to implement robust security measures to ensure compliance and data protection.

Here are some options you can consider as per Security considerations for data movement in Azure Data Factory:

Data Encryption

• At Rest: Ensure data is encrypted at rest using Azure's built-in encryption capabilities. Azure Storage accounts, Azure SQL Database, and Data Lake Storage support encryption at rest by default using Azure Storage Service Encryption (SSE).
• In Transit: Use HTTPS for secure communication to ensure data is encrypted during transit. ADF supports Secure Transfer Required (HTTPS) for all data movements.

Data Masking and Anonymization

• Data Masking in Azure SQL Database: If you're storing data in Azure SQL Database, consider using Dynamic Data Masking to limit sensitive data exposure by masking it to non-privileged users.
• Dataflow Transformation in ADF: Although handling large amounts of data can be challenging, you can use mapping data flows in ADF to perform data masking and anonymization. This might involve creating custom transformations to apply masking rules or leveraging built-in functions for hashing or encryption.
• Azure Data Share: Use Azure Data Share with snapshot-based sharing for scenarios requiring controlled and masked data sharing.

Data Governance and Classification

• Azure Purview: Use Azure Purview to classify and catalog sensitive data across your data estate. This helps in tracking data lineage and applying policies for data protection.
• Azure Policy: Use Azure Policy to enforce compliance and governance across your Azure resources, ensuring sensitive data is managed according to your organization's standards.

Third-Party Tools

• Informatica: Informatica's Cloud Data Integration can be integrated with ADF to provide advanced data masking and anonymization capabilities.
• Protegrity or IBM Guardium: These tools offer data protection and masking solutions that can be integrated into your data pipeline for enhanced security and compliance.

Managed Private Endpoints

• Private Link: Use Azure Private Link to secure the data transfer between ADF and other Azure services, ensuring that your data traffic remains within the Azure network without exposure to the public internet.
• Virtual Network Integration: Integrate ADF with a Virtual Network (VNet) to secure the traffic between ADF and your on-premises or cloud resources.

Access Control and Monitoring

• Role-Based Access Control (RBAC): Ensure that only authorized users have access to sensitive data and ADF pipelines. Use RBAC to control access to resources.
• Azure Monitor and Azure Sentinel: Implement monitoring and logging for data access and movement within ADF pipelines. Azure Sentinel can help detect and respond to potential security threats in real-time.

Compliance Considerations

• Review Azure’s compliance offerings to ensure your implementation meets relevant standards such as GDPR, HIPAA, or other regional regulations.
• Conduct regular audits and assessments to ensure that all sensitive data handling processes adhere to required compliance standards.

By leveraging these options, you can create a secure, compliant, and efficient data processing environment within Azure Data Factory, while addressing the challenges of dealing with sensitive data.

Hope this helps. Do let us know if you any further queries.

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