Data obfuscation hides the original content of data to protect identities and personal information.
Data obfuscation is frequently utilized interchangeably with data masking. Data obfuscation scrambles data in order to anonymize it. Data obfuscation is fundamental in many regulated industries where personally identifiable data must be shielded from overexposure.
As with data masking, special care should be taken in the use of obfuscation for de-identifying data. Even with identity information obfuscated, key data elements such as age, zip code, and sex may allow for individuals to be re-identified.
What are some examples of data obfuscation?
- First and last names are randomized to protect identity.
- A credit card number is presented as all zeros.
- Diagnostic codes are presented as all X’s.
How can organizations implement obfuscation via data masking?
- Custom scripts: Programmers write custom scripts to modify data fields related to personal or sensitive data.
- Packaged software: These data masking software tools and solutions provide templates for typical masking tasks (such as credit cards, SSN, phone) and support data sources typically found across the enterprise including cloud, Hadoop, relational, mainframe, and file systems.
- Data management software: Some data integration and data management software have the ability to transform or anonymize personal or sensitive data fields.
Which departments or business functions are most likely to use obfuscation via data masking?
- Operations: For customer service representatives who only need partial sets of personal information to do their job.
- DevOps: Data masking can anonymize datasets for application testers to ensure that no private data is shared with internal or external testing or quality assurance teams.
- Analytics: Personal data with no relevant or authorized analytics purpose can be masked to limit privacy and security risks.