ANONYM.COMMUNITY
anonym.plus SD1 LINKABILITY
Case Study 12 of 20

An Algorithmic Pipeline for GDPR-Compliant Healthcare Data Anonymisation: Moving Toward Standardisation

Hamza Khan, Lore Menten, Liesbet M. Peeters · 2025-06

Research Source

An Algorithmic Pipeline for GDPR-Compliant Healthcare Data Anonymisation: Moving Toward Standardisation
Hamza Khan, Lore Menten, Liesbet M. Peeters · arxiv · 2025-06

High-quality real-world data (RWD) is essential for healthcare but must be transformed to comply with the General Data Protection Regulation (GDPR). GDPRs broad definitions of quasi-identifiers (QIDs) and sensitive attributes (SAs) complicate implementation. We aim to standardise RWD anonymisation…

Executive Summary

This research paper examines a critical privacy challenge related to LINKABILITY — the ability to connect two pieces of information to the same person.

anonym.plus addresses this through 200+ entity types with multi-layer detection accessible across Desktop App (Windows/macOS/Linux) and additional platforms.

Root Cause: SD1 — LINKABILITY

The ability to connect two pieces of information to the same person. This is the foundational operation that makes PII dangerous. Nearly every pain point is an expression of linkability being created, exploited, or failing to be broken.

Irreducible truth: You cannot have useful data that is completely unlinkable AND completely useful. The very features that make data informative make it linkable. This is not a bug — it is information theory. The information content of a dataset and its linkability are the same property measured differently.

The Solution: How anonym.plus Addresses This

Detection Capabilities

anonym.plus identifies 200+ entity types including names, emails, SSNs, IBANs, passports, medical records, and country-specific identifiers. The local Presidio 2.2.357 + spaCy 3.8.11 architecture runs entirely offline — no cloud uploads, no internet required for detection. Supports 38 OCR languages via Tesseract for image anonymization.

Anonymization Methods

Redact is recommended for this pain point: completely removing fingerprint-contributing values eliminates the data points that algorithms combine into unique identifiers. Replace provides an alternative — substituting with non-unique alternatives prevents cross-device correlation while preserving document readability. For scenarios requiring reversibility, Encrypt (AES-256-GCM) enables authorized recovery of original values.

Architecture & Deployment

The REST API (Basic plan+) provides programmatic PII detection with Bearer token auth — the most accessible API entry point in the ecosystem.

Compliance Mapping

This pain point intersects with GDPR Article 5(1)(c) data minimization, ePrivacy Directive tracking consent.

anonym.plus's GDPR, HIPAA compliance coverage, combined with Fully offline — no server hosting, provides documented technical measures organizations can reference in their compliance documentation and regulatory submissions.

Product Specifications

SpecificationValue
Platform Version1.0.0 (desktop)
Entity Types200+
Accuracy95%+ (offline NLP)
Languages38 (OCR), 20+ (NLP)
Anonymization MethodsReplace, Redact, Mask, Hash (SHA-256), Encrypt (AES-256-GCM reversible)
PlatformsDesktop App (Windows/macOS/Linux)
PricingFree, Basic €149, Pro €399, Expert €499 (one-time lifetime)
HostingFully offline — no server
ComplianceGDPR, HIPAA