Dashboard Structural Analysis cloak.business SD2 IRREVERSIBILITY Case Study
← Previous Next →
cloak.business SD2 IRREVERSIBILITY
Case Study 18 of 30

Clinical de-identification using sub-document analysis and ELECTRA

Rosario Catelli, F. Gargiulo, Emanuele Damiano et al. · International Conference on Digital Health (2021-09-01)

Research Source

Clinical de-identification using sub-document analysis and ELECTRA
Rosario Catelli, F. Gargiulo, Emanuele Damiano et al. · International Conference on Digital Health · 2021-09-01 · Source: semantic_scholar

The privacy protection mechanism in the health context is becoming a crucial task given the exponential increase in the adoption of the Electronic Health Records (EHRs) all around the world. This kind of data can be used for medical investigation and research only if it is filtered out of all the so called Protected Health Information (PHI).

Executive Summary

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

cloak.business addresses this through zero-storage microservices processing all data in-memory with no disk writes — PII cannot propagate from a system that never stores it.

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 cloak.business Addresses This

Detection Capabilities

cloak.business identifies 390+ entity types including email addresses, passwords, usernames, IP addresses, account identifiers. The dual-layer (317 custom regex + NLP) architecture uses 317 custom regex recognizers with context word analysis and confidence scoring 0.0–1.0 for structured identifiers and spaCy (25 languages) + Stanza (7 languages) + XLM-RoBERTa (16 languages) — all self-hosted for contextual references.

Anonymization Methods

Encrypt is recommended for this pain point: AES-256-GCM encryption of credentials in documents enables authorized access for incident response while protecting at rest. Hash provides an alternative — SHA-256 hashing enables breach impact analysis without exposing original values. For permanent removal, Redact ensures data cannot be recovered under any circumstances.

Architecture & Deployment

Zero-storage microservices with self-hosted NLP models (spaCy, Stanza, XLM-RoBERTa). All processing in-memory on German servers. No data ever written to disk, no third-party transfers.

Compliance Mapping

This pain point intersects with GDPR Articles 33-34 breach notification, Article 32 security measures.

cloak.business’s GDPR (Article 25 Privacy by Design), ISO 27001:2022 compliance coverage, combined with Germany only, no third-party transfers, ISO 27001:2022 certified hosting, provides documented technical measures organizations can reference in their compliance documentation and regulatory submissions.

Product Specifications

SpecificationValue
Platform VersionAnalyzer 6.9.1, Image Redactor 5.3.0
Entity Types390+ (519 documented)
Detection Layers317 custom regex + 3 NLP engines (all self-hosted)
Languages48 UI languages, 37 OCR language packs
Anonymization MethodsReplace, Redact, Mask, Hash (SHA-256), Encrypt (AES-256-GCM)
ArchitectureZero-storage microservices (in-memory only)
Integration PointsWeb App, Desktop, Office Add-in, MCP Server (9 tools), REST API
HostingGermany only, ISO 27001:2022, no third-party transfers
ComplianceGDPR Article 25, ISO 27001:2022
← Previous Next →