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Black Box Methodology for Technical Compliance with the EU AI Act

Ahmad Qasim Mohammad Hassan

ORCID License: CC BY-NC-ND 4.0 DOI Compliance Portal


Overview

This paper presents a technical compliance methodology that addresses a fundamental gap in EU AI Act enforcement: regulatory authorities currently rely on self-assessment documentation without any independent technical tool to verify compliance, while direct access to corporate infrastructure is constrained by trade secret obligations.

The proposed approach requires companies to establish an internal compliance layer – embedded within existing infrastructure – that continuously monitors system behavior, records every violation in a tamper-protected cryptographic log, and automatically sends a minimal three-field alert to regulatory authorities upon any breach, without disclosing operational data or trade secrets.

Regulation (EU) 2024/1689 – Articles 5, 9-15, 50, 53, 55


Licensed Deliverables

The complete article-by-article technical translation — every paragraph of Articles 5, 9–15, 50, 53, and 55 mapped to a technically verifiable requirement with a peer-reviewed scientific basis — has been fully completed and is available for licensing.

Deliverable Description
Technical Translation Full article-by-article translation of legal provisions into verifiable technical requirements, grounded in peer-reviewed literature (ACM, IEEE, ISO, NIST).
Implementation Architecture Conceptual four-layer enforcement architecture (interception, rule engine, behavioral monitor, immutable audit) illustrating technical feasibility — provided for expert review and engineering implementation.

Licensing: Institutions, regulators, and organisations building AI compliance infrastructure can select the relevant articles for their sector through the live Compliance Portal, or request licensing terms directly from the author.


Compliance Portal

Compliance Portal

The portal allows organisations to filter the methodology by institutional sector (LegalTech, Healthcare AI, Financial Services, HR & Recruitment, Autonomous Vehicles, GPAI Providers, and others) and request licensing for the specific articles relevant to their systems.


Scientific Basis

The methodology translates ten articles of the EU AI Act into technically verifiable requirements grounded in 68 peer-reviewed references and verified standards from ACM, IEEE, ISO, NIST, Oxford, Harvard, Stanford CRFM, Anthropic, Nature, and Science Advances.


Author

Ahmad Qasim Mohammad Hassan Independent Security Researcher

LinkedIn · ORCID

© 2026 Ahmad Qasim Mohammad Hassan. Licensed under CC BY-NC-ND 4.0.

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Technical compliance methodology for translating EU AI Act obligations into verifiable requirements embedded in AI infrastructure.

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