DRPV-12

Do you "anonymize," "de-identify," or otherwise mask personal data?

Explanation

This question is asking whether your organization takes steps to protect personal data by removing or obscuring identifying information. 'Anonymization' means permanently removing all identifying information from data so that it cannot be linked back to individuals. 'De-identification' is similar but may allow for re-identification with additional information (often through a key kept separate from the data). 'Masking' refers to hiding certain portions of data while keeping the format intact (like showing only the last 4 digits of a credit card). This question is being asked in a security assessment because protecting personal data is a key requirement of many privacy regulations (like GDPR, CCPA, HIPAA). Organizations that process personal data are expected to minimize privacy risks by only retaining identifying information when absolutely necessary. To best answer this question, you should: 1. Clearly state whether you use anonymization, de-identification, or masking techniques 2. Explain which techniques you use and in which contexts 3. Describe your processes for determining when and how to apply these techniques 4. Mention any standards or frameworks you follow for these processes 5. Note any exceptions where you cannot mask personal data and why

Example Responses

Example Response 1

Yes, our organization employs multiple data protection techniques For analytics and reporting purposes, we anonymize personal data by removing all direct identifiers (names, emails, etc.) and applying k-anonymity techniques to prevent re-identification through indirect identifiers For development and testing environments, we use data masking to replace sensitive information with realistic but fictional data while maintaining referential integrity We follow NIST SP 800-122 guidelines for de-identification and have documented procedures for determining appropriate techniques based on data sensitivity classification All anonymization processes are validated by our privacy team before implementation.

Example Response 2

Yes, we implement de-identification for research data and data masking for production data Our de-identification process involves removing 18 HIPAA-defined identifiers from health information and replacing them with pseudonyms when longitudinal data tracking is required For production systems, we employ dynamic data masking that restricts sensitive data visibility based on user roles and access privileges Our Data Governance Committee reviews and approves all de-identification methodologies, and we conduct regular risk assessments to evaluate the effectiveness of our techniques against re-identification attempts We maintain a data dictionary that tracks original-to-masked value mappings in a highly secured environment accessible only to authorized personnel.

Example Response 3

No, we do not currently anonymize, de-identify, or mask personal data in our systems Our application requires full access to personal information to deliver its core functionality of personalized healthcare recommendations We've determined that anonymizing or masking this data would significantly degrade service quality and user experience Instead, we focus on strong access controls, encryption, and strict data handling policies to protect personal information We're exploring potential techniques for partial data masking in non-production environments but haven't implemented these yet due to technical limitations in our current architecture.

Context

Tab: Privacy
Category: Data Privacy