Pseudonymisation Patterns Expert
Design and implement GDPR-compliant pseudonymisation systems using tokenization, encryption, hashing, and data masking patterns with re-identification risk assessment.
SupaScore
83.5Best for
- ▸GDPR Article 4(5) compliant pseudonymisation system architecture for customer analytics
- ▸Medical device HIPAA pseudonymisation with re-identification risk assessment
- ▸Financial services PCI DSS tokenization vault implementation with format-preserving encryption
- ▸Multi-jurisdiction data sharing with k-anonymity and l-diversity statistical disclosure control
- ▸Cross-border clinical trial data pseudonymisation meeting EMA and FDA requirements
What you'll get
- ●Technical architecture diagram with tokenization vault, HMAC-SHA-256 pseudonym generation, and k≥5 anonymity validation for each data processing stage
- ●Risk assessment matrix quantifying re-identification probability using Sweeney's k-anonymity model with specific mitigation controls
- ●Implementation code patterns for AES-256 format-preserving encryption with NIST FF1/FF3-1 standards and key rotation procedures
Not designed for ↓
- ×Full data anonymisation (irreversible removal of all identifiers)
- ×Generic encryption of data at rest or in transit without pseudonymisation patterns
- ×Basic password hashing or salting for authentication systems
- ×Legal interpretation of GDPR recitals or regulatory compliance advice
Detailed data inventory with direct/quasi-identifiers, processing purposes, data flows, and specific regulatory requirements (GDPR, HIPAA, PCI DSS).
Complete technical architecture with pseudonymisation technique selection, implementation patterns, re-identification risk metrics, and regulatory compliance mapping.
Evidence Policy
Enabled: this skill cites sources and distinguishes evidence from opinion.
Research Foundation: 7 sources (3 official docs, 2 paper, 1 academic, 1 industry frameworks)
This skill was developed through independent research and synthesis. SupaSkills is not affiliated with or endorsed by any cited author or organisation.
Version History
Initial release
Prerequisites
Use these skills first for best results.
Works well with
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Common Workflows
Privacy-Compliant Analytics Pipeline
Map personal data inventory, implement pseudonymisation controls, then audit for regulatory compliance before production deployment
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