Award date: 15 June 2023 Supervisor: Prof. Andrea Renda (European University Institute) The responsibility for regulating emerging technologies such as AI is falling into the hands of the Data Protection Regulators as responsibility is attributed to them through the AI Act.
This research paper examines a critical privacy challenge related to KNOWLEDGE ASYMMETRY — the gap between what is known and what is practiced.
anonymize.solutions addresses this through 13 educational resources, 10 demo platforms, and MCP Server (7 tools) embedding PII awareness directly into developer workflows.
The gap between what is known and what is practiced. Solutions exist in papers that practitioners never read. Attacks are documented that defenders never learn about. Rights exist that individuals never exercise.
Irreducible truth: Every other structural driver could theoretically be mitigated if knowledge were perfect and universally distributed. But knowledge is never perfect and never universal. This gap is the reason known solutions aren't applied, known attacks aren't defended against, and known rights aren't exercised.
anonymize.solutions identifies 260+ entity types including MPC keys, FHE parameters, ZKP data, cryptographic configurations. The dual-layer (regex + NLP) architecture uses 210+ custom pattern recognizers (246 patterns, 75+ country formats, checksum-validated) for structured identifiers and spaCy (25 languages) + Stanza (7 languages) + XLM-RoBERTa (16 languages) for contextual references.
Redact is recommended for this pain point: providing practical, deployable anonymization today addresses the gap while MPC/FHE/ZKP remain in academic development. Replace provides an alternative — replacing PII with anonymized alternatives is immediately deployable, unlike MPC/FHE/ZKP requiring infrastructure changes. For scenarios requiring reversibility, Encrypt (AES-256-GCM) enables authorized recovery of original values.
The REST API integrates into data pipelines (n8n, Make, Zapier) for automated PII anonymization before data reaches downstream systems. Three deployment models — SaaS (token pay-per-use), Managed Private (customer key management), and Self-Managed (Docker, air-gapped) — match any infrastructure requirement.
This pain point intersects with GDPR Article 25 data protection by design, Article 32 state-of-the-art measures.
anonymize.solutions’s GDPR, HIPAA, FERPA, PCI-DSS, ISO 27001 compliance coverage, combined with 100% EU (Hetzner Germany, ISO 27001) hosting, provides documented technical measures organizations can reference in their compliance documentation and regulatory submissions.
| Specification | Value |
|---|---|
| Product Version | v1.6.12 |
| Entity Types | 260+ |
| Detection Layers | Dual-layer: 210+ regex recognizers + 3 NLP engines |
| Languages | 48 (spaCy 25, Stanza 7, XLM-RoBERTa 16) |
| Anonymization Methods | Replace, Redact, Mask, Hash (SHA-256), Encrypt (AES-256-GCM) |
| Deployment Options | SaaS, Managed Private, Self-Managed (Docker/Air-Gapped) |
| Integration Points | REST API, MCP Server, Office Add-in, Desktop App, Chrome Extension |
| Hosting | 100% EU (Hetzner Germany, ISO 27001) |
| Compliance | GDPR, HIPAA, FERPA, PCI-DSS, ISO 27001 |