anonym.plus SD2 IRREVERSIBILITY
Case Study 17 of 30

Privacy in Italian Clinical Reports: A NLP-Based Anonymization Approach

Tobia Giovanni Paolo, Patarnello Stefano, Masciocchi Carlotta et al. · 2025 IEEE 13th International Conference on Healthcare Informatics (ICHI) (2025-06-18)

Research Source

Privacy in Italian Clinical Reports: A NLP-Based Anonymization Approach
Tobia Giovanni Paolo, Patarnello Stefano, Masciocchi Carlotta et al. · 2025 IEEE 13th International Conference on Healthcare Informatics (ICHI) · 2025-06-18 · Source: openaire

The sharing of data is of significant importance for the advancement of scientific and technological knowledge. However, legislation such as the General Data Protection Regulation (GDPR) in Europe and the Health Insurance Portability and Accountability Act (HIPAA) in the United States implies significant restrictions on the dissemination of personal data within the healthcare sector.

Executive Summary

This research paper examines a critical privacy challenge related to IRREVERSIBILITY — once pii propagates, it cannot be un-propagated.

anonym.plus addresses this through 100% local processing with AES-256-GCM encrypted vault — PII processed and stored locally, never touching any external server.

Root Cause: SD2 — IRREVERSIBILITY

Once PII propagates, it cannot be un-propagated. The arrow of data only points one direction. PII exposure is a one-way function with no inverse.

Irreducible truth: Information entropy only increases. You cannot recall a broadcast signal. You cannot un-train a neural network. You cannot selectively erase a backup tape. Every deletion mechanism is an approximation — and the original exposure persists.

The Solution: How anonym.plus Addresses This

Detection Capabilities

anonym.plus identifies 200+ entity types including names, addresses, contact details, identifying descriptions, biographical information. The local Presidio 2.2.357 + spaCy 3.8.11 architecture uses Presidio 2.2.357 deterministic recognizers with 121 built-in presets for structured identifiers and spaCy 3.8.11 with 23 language models, all running locally via FastAPI sidecar for contextual references.

Anonymization Methods

Redact is recommended for this pain point: anonymizing documents at creation prevents PII from appearing in any cached, indexed, or archived copy. Replace provides an alternative — substituting identifiers before publication ensures cached copies contain only anonymized data. For scenarios requiring reversibility, Encrypt (AES-256-GCM) enables authorized recovery of original values.

Architecture & Deployment

The Tauri 2.x desktop application (Rust + React) processes 7 document formats (PDF, DOCX, XLSX, TXT, CSV, JSON, XML) plus images (Tesseract OCR). AES-256-GCM vault with Argon2id protects all stored data.

Compliance Mapping

This pain point intersects with GDPR Article 17 right to erasure, Article 17(2) obligation to inform recipients.

anonym.plus’s GDPR (data never leaves device), HIPAA (local processing) compliance coverage, combined with 100% local — data never leaves device hosting, provides documented technical measures organizations can reference in their compliance documentation and regulatory submissions.

Product Specifications

Specification Value
App Version v8.10.5
Entity Types 200+ built-in, up to 50 custom
Detection Engine Presidio 2.2.357 + spaCy 3.8.11 (23 models)
Languages 48 UI, 23 NLP models
Document Formats PDF, DOCX, XLSX, TXT, CSV, JSON, XML + Image OCR
Anonymization Methods Replace, Redact, Mask, Hash (SHA-256/512/MD5), Encrypt (AES-256-GCM)
Architecture Tauri 2.x (Rust + React) + FastAPI sidecar (~370 MB)
Platforms Win/Mac/Linux
Licensing Ed25519 signed, machine-fingerprinted, max 5 machines
Processing 100% local — data never leaves device
Compliance GDPR, HIPAA (data residency guaranteed by local processing)

Research Limitations

Academic Scope: This summary reflects findings from the original academic research paper. Implementation contexts, regulatory landscapes, and technical capabilities may have evolved since publication. Readers should verify current best practices and compliance requirements in their jurisdiction.

Generalizability: Research findings may be specific to the studied populations, geographic regions, or technical environments described in the original paper. Organizations should evaluate applicability to their specific use case before adopting recommendations.

Not a Substitute for Legal/Compliance Advice: This research summary is provided for informational and educational purposes only. It does not constitute legal, compliance, or professional consulting advice. Consult qualified privacy counsel for GDPR, HIPAA, CCPA, or other regulatory compliance guidance.