{
  "id": "SD1-09-the-lawfulness-of-re-identification-under-data-protection-la",
  "type": "case-study",
  "title": "The lawfulness of re-identification under data protection law",
  "description": "Research-backed case study: The lawfulness of re-identification under data protection law. Analysis of LINKABILITY structural driver and how anonym.legal…",
  "url": "https://anonym.community/anonym.legal/SD1-09-the-lawfulness-of-re-identification-under-data-protection-la.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": "Teodora Curelariu, Alexandre Lodie · APF · 2024-09-04 · Source: hal\n\nData re-identification methods are becoming increasingly sophisticated and can lead to disastrous data breaches. Re-identification is a key research topic for computer scientists as it can be used to reveal vulnerabilities of de-identification methods such as anonymisation or pseudonymisation. However, re-identification, even for research purposes, involves processing personal data."
      },
      {
        "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 advertising IDs, cookie identifiers, browsing interests, location markers, bid request parameters. 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 PII before it enters advertising pipelines prevents the 376-times-daily broadcast of personal information. Replace provides an alternative — substituting identifiers with non-trackable alternatives enables advertising analytics without individual targeting. 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 6 lawful basis, ePrivacy Directive consent for tracking, Article 7 consent conditions.\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": "SD1-03: 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": "SD1-10: 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/SD1-09-the-lawfulness-of-re-identification-under-data-protection-la.html"
    },
    {
      "label": "cloak.business",
      "url": "../cloak.business/SD1-09-the-lawfulness-of-re-identification-under-data-protection-la.html"
    },
    {
      "label": "anonym.plus",
      "url": "../anonym.plus/SD1-09-the-lawfulness-of-re-identification-under-data-protection-la.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"
  }
}