{ "id": "SD1-02-autononym-multimodal-anonymization-of-health-data-using-name", "type": "case-study", "title": "Autononym: Multimodal Anonymization of Health Data using Named Entity Recognition and Structured Medical Data Processing", "description": "Research-backed case study: Autononym: Multimodal Anonymization of Health Data using Named Entity Recognition and Structured Medical Data Processi [.legal]", "url": "https://anonym.community/anonym.legal/SD1-02-autononym-multimodal-anonymization-of-health-data-using-name.html", "product": "anonym.legal", "driver": { "id": 1, "name": "LINKABILITY" }, "breadcrumbs": [ { "label": "Dashboard", "url": "https://anonym.community/../dashboard.html" }, { "label": "Structural Analysis", "url": "https://anonym.community/../structural-analysis.html" }, { "label": "anonym.legal", "url": "https://anonym.community/index.html" }, { "label": "SD1 LINKABILITY", "url": "https://anonym.community/index.html#SD1" } ], "content": { "sections": [ { "type": "summary", "heading": "Research Source", "content": "Hamdi Yalin Yalic, Murat Dörterler, Alaettin Uçan et al. · Medical Technologies National Conference · 2025-10-26 · Source: semantic_scholar\n\nThis paper presents Autononym, an AI-powered software platform capable of robustly and scalably anonymizing health data across several formats, including unstructured free-text documents, tabular datasets, and medical images in both DICOM and standard RGB formats." }, { "type": "summary", "heading": "Executive Summary", "content": "This research paper examines a critical privacy challenge related to LINKABILITY — the ability to connect two pieces of information to the same person.\n\nanonym.legal addresses this through 260+ entity types with 3-layer hybrid detection accessible via 6 platforms including Chrome Extension for real-time browser anonymization." }, { "type": "problem", "heading": "Root Cause: SD1 — LINKABILITY", "content": "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.\n\nIrreducible 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.", "atomicTruth": "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." }, { "type": "solution", "heading": "The Solution: How anonym.legal Addresses This", "content": "anonym.legal identifies 260+ entity types including zip codes, dates of birth, gender markers, demographic quasi-identifiers. The 3-layer hybrid (Presidio + NLP + Stance classification) architecture uses Microsoft Presidio deterministic rules with checksum validations (Luhn, RFC-822) for structured identifiers and XLM-RoBERTa + Stanza NER with Stance classification for disambiguation for contextual references.\n\nHash is recommended for this pain point: deterministic SHA-256 hashing enables referential integrity across datasets while preventing re-identification from original values. Replace provides an alternative — substituting quasi-identifiers with type labels removes re-identification potential while preserving data structure. For scenarios requiring reversibility, Encrypt (AES-256-GCM) enables authorized recovery of original values.\n\nThe REST API (Basic plan+, €3/month) provides programmatic PII detection with Bearer token auth. Rate limited to 100 req/min, max 100 KB per request — the most accessible API entry point in the ecosystem." }, { "type": "compliance", "heading": "Compliance Mapping", "content": "This pain point intersects with GDPR Recital 26 identifiability test, Article 89 research safeguards.\n\nanonym.legal’s GDPR, HIPAA, PCI-DSS, ISO 27001 compliance coverage, combined with Hetzner Germany, ISO 27001 certified hosting, provides documented technical measures organizations can reference in their compliance documentation and regulatory submissions." }, { "type": "specifications", "heading": "Product Specifications", "specs": { "Platform Version": "v7.4.4", "Entity Types": "260+", "Detection Layers": "3-layer: Presidio + NLP + Stance classification", "Accuracy": "95.5% tested (42/44 tests)", "Languages": "48", "Anonymization Methods": "Replace, Redact, Mask, Hash (SHA-256/512/MD5), Encrypt (AES-256-GCM)", "Platforms": "Web App, Desktop, Office Add-in, MCP Server, Chrome Extension, REST API", "Pricing": "Free €0, Basic €3, Pro €15, Business €29", "Hosting": "Hetzner Germany, ISO 27001", "Compliance": "GDPR, HIPAA, PCI-DSS, ISO 27001" } } ] }, "relatedLinks": [ { "label": "SD1-01: TÉCNICAS PARA ANONIMIZAR DADOS SENSÍVEIS EM SISTEMAS DE INFORMAÇÃO", "url": "SD1-01-tcnicas-para-anonimizar-dados-sensveis-em-sistemas-de-inform.html" }, { "label": "SD1-03: OpenAIRE webinar - Amnesia: High-accuracy Data Anonymization", "url": "SD1-03-openaire-webinar-amnesia-high-accuracy-data-anonymization.html" }, { "label": "SD1-04: Anonymizing Machine Learning Models", "url": "SD1-04-anonymizing-machine-learning-models.html" }, { "label": "SD1-05: Towards formalizing the GDPR's notion of singling out.", "url": "SD1-05-towards-formalizing-the-gdprs-notion-of-singling-out.html" }, { "label": "SD1-06: From t-closeness to differential privacy and vice versa in data anonymization", "url": "SD1-06-from-t-closeness-to-differential-privacy-and-vice-versa-in-d.html" }, { "label": "SD1-07: A Survey on Current Trends and Recent Advances in Text Anonymization", "url": "SD1-07-a-survey-on-current-trends-and-recent-advances-in-text-anony.html" }, { "label": "SD1-08: Reconsidering Anonymization-Related Concepts and the Term “Identification” Against the Backdrop of the European Legal Framework", "url": "SD1-08-reconsidering-anonymization-related-concepts-and-the-term-id.html" }, { "label": "SD1-09: The lawfulness of re-identification under data protection law", "url": "SD1-09-the-lawfulness-of-re-identification-under-data-protection-la.html" }, { "label": "SD1-10: Blinded Anonymization: a method for evaluating cancer prevention programs under restrictive data protection regulations", "url": "SD1-10-blinded-anonymization-a-method-for-evaluating-cancer-prevent.html" }, { "label": "anonymize.solutions", "url": "../anonymize.solutions/SD1-02-autononym-multimodal-anonymization-of-health-data-using-name.html" }, { "label": "cloak.business", "url": "../cloak.business/SD1-02-autononym-multimodal-anonymization-of-health-data-using-name.html" }, { "label": "anonym.plus", "url": "../anonym.plus/SD1-02-autononym-multimodal-anonymization-of-health-data-using-name.html" }, { "label": "Download SD1 LINKABILITY PDF (all 10 case studies)", "url": "#" }, { "label": "Back to anonym.legal Index", "url": "index.html" }, { "label": "Structural Analysis", "url": "../structural-analysis.html" }, { "label": "Cross-Domain Analysis", "url": "../structural-analysis.html" }, { "label": "Dashboard", "url": "../dashboard.html" } ], "metadata": { "lastModified": "2026-03-14" } }