GDPR Anonymizer

The GDPR Anonymizer provides comprehensive protection for personal and sensitive data through multiple anonymization methods. It ensures GDPR compliance while maintaining data utility for analysis.

Data anonymization workflow and protection levels

Privacy Notice: Ensure proper configuration of anonymization rules to maintain GDPR compliance. Regular audits of anonymization patterns are recommended.

Anonymization Actions

Hash

Input: john.doe@email.com
Output: 5e8ff9bf55ba3508199d22e984129be6

Replace

Input: John Doe
Output: James Smith

Redact

Input: 123-45-6789
Output: [REDACTED]

Mask

Input: 123-456-7890
Output: ***-***-7890

Protected Entities

Personal Data

Names
Email Addresses
Phone Numbers
Social Security Numbers
Credit Card Numbers
Passport Numbers

Location Data

Physical Addresses
ZIP/Postal Codes
GPS Coordinates
IP Addresses
Country Codes

Configuration Options

action: Anonymization method to apply
entities: List of entities to protect
consistency: Maintain consistent anonymization
language: Target language support
custom_patterns: User-defined patterns

Example Usage

const anonymizer = new GDPRAnonymizer({
  action: 'mask',
  entities: ['email', 'phone', 'name'],
  consistency: true,
  language: 'en'
});

const result = anonymizer.anonymize(
  "Contact John Doe at john.doe@email.com"
);

// Output: "Contact J*** D** at j***.d**@email.com"

Features

Multiple anonymization methods
Pattern-based entity detection
Consistent anonymization
Multi-language support
Custom entity definitions
Audit logging
GDPR compliance verification

Note: The anonymizer maintains a balance between data privacy and utility. Choose appropriate anonymization methods based on your specific use case and compliance requirements.

Tip: Regularly update your entity patterns and test anonymization effectiveness with sample data. Consider implementing additional security measures for highly sensitive data.