{
  "id": "SD1-03-openaire-webinar-amnesia-high-accuracy-data-anonymization",
  "type": "case-study",
  "title": "OpenAIRE webinar - Amnesia: High-accuracy Data Anonymization",
  "description": "Research-backed case study: OpenAIRE webinar - Amnesia: High-accuracy Data Anonymization. Analysis of LINKABILITY structural driver and how anonym.legal…",
  "url": "https://anonym.community/anonym.legal/SD1-03-openaire-webinar-amnesia-high-accuracy-data-anonymization.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": "Terrovitis, Manolis · 2023-02-10 · Source: openaire\n\nThe webinar will introduce the concept of anonymization of research data, including direct identifiers and quasi-identifiers using Amnesia, which is a flexible data anonymization tool that transforms sensitive data to datasets where formal privacy guarantees hold. Amnesia transforms original data to provide k-anonymity and km-anonymity."
      },
      {
        "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 email addresses, timestamps, IP addresses, communication metadata, geolocation markers. 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\nRedact is recommended for this pain point: removing metadata fields entirely prevents correlation attacks that link communication patterns to individuals. Mask provides an alternative — partial masking preserves format for system compatibility while breaking linkability. 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 Article 5(1)(f) integrity and confidentiality, ePrivacy Directive metadata restrictions.\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": "SD1-02: Autononym: Multimodal Anonymization of Health Data using Named Entity Recognition and Structured Medical Data Processing",
      "url": "SD1-02-autononym-multimodal-anonymization-of-health-data-using-name.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/SD1-03-openaire-webinar-amnesia-high-accuracy-data-anonymization.html"
    },
    {
      "label": "cloak.business",
      "url": "../cloak.business/SD1-03-openaire-webinar-amnesia-high-accuracy-data-anonymization.html"
    },
    {
      "label": "anonym.plus",
      "url": "../anonym.plus/SD1-03-openaire-webinar-amnesia-high-accuracy-data-anonymization.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"
  }
}