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ISO/IEC 24029-2:2023

International
vISO/IEC 24029-2:2023, first edition (2023-08)
3 domains
18 controls

ISO/IEC's methodology for proving the robustness of neural networks with formal methods: define the domain by bounded attributes, express stability, sensitivity, relevance and reachability criteria, choose solvers, abstract interpretation, reachability analysis or model checking to fit the network, and apply them from design through verification, deployment and operation.

Verified

ISO/IEC 24029-2:2023 is a compliance framework from International with 3 domains and 18 controls. The largest domains are Clause 5: Robustness properties and criteria (domain, stability, sensitivity, relevance, reachability) – ISO/IEC 24029-2:2023 (8 controls), Clause 7: Robustness assessment through the AI system life cycle – ISO/IEC 24029-2:2023 (7 controls), Clause 6: Choosing formal methods that fit the network and its data – ISO/IEC 24029-2:2023 (3 controls). Every control below carries what it requires and what an assessor expects to see.

Maintained by Gerard Blokdyk

Framework summaries on this platform are interpretations grounded in the published source, for educational and compliance planning purposes. They do not reproduce or replace the official standards. Refer to the authoritative source for the definitive text. Framework names and trademarks belong to their respective organisations.

Framework Domains (3)

Clause 5: Robustness properties and criteria (domain, stability, sensitivity, relevance, reachability) – ISO/IEC 24029-2:2023

8 controls
Controls in the Clause 5: Robustness properties and criteria (domain, stability, sensitivity, relevance, reachability) – ISO/IEC 24029-2:2023 domain of ISO/IEC 24029-2:2023: 8 controls
CodeTitle
iso-iec-24029-2-2023::5.2Specify the domain of use through bounded attributes
iso-iec-24029-2-2023::5.3.1Express a stability property where noisy inputs must not change the output
iso-iec-24029-2-2023::5.3.2Define and apply a stability criterion
iso-iec-24029-2-2023::5.4.1Carry out sensitivity analysis over a domain
iso-iec-24029-2-2023::5.4.2Define and apply a sensitivity criterion
iso-iec-24029-2-2023::5.5.1Use a relevance property where a human could do the task
iso-iec-24029-2-2023::5.5.2Define and apply a relevance criterion
iso-iec-24029-2-2023::5.6Express and satisfy a reachability criterion for closed-loop agents

Clause 6: Choosing formal methods that fit the network and its data – ISO/IEC 24029-2:2023

3 controls
Controls in the Clause 6: Choosing formal methods that fit the network and its data – ISO/IEC 24029-2:2023 domain of ISO/IEC 24029-2:2023: 3 controls
CodeTitle
iso-iec-24029-2-2023::6.1Match the formal method to the network architecture and input data type
iso-iec-24029-2-2023::6.2.1Classify and choose verifiers by completeness, determinism, model access and arithmetic
iso-iec-24029-2-2023::6.2.6Check every model when model checking is used

Clause 7: Robustness assessment through the AI system life cycle – ISO/IEC 24029-2:2023

7 controls
Controls in the Clause 7: Robustness assessment through the AI system life cycle – ISO/IEC 24029-2:2023 domain of ISO/IEC 24029-2:2023: 7 controls
CodeTitle
iso-iec-24029-2-2023::7.2.2Identify the features the network has learned with a relevance criterion
iso-iec-24029-2-2023::7.2.3Check class separability with a sensitivity criterion
iso-iec-24029-2-2023::7.3.2Bound and justify the parts of the input domain covered at verification
iso-iec-24029-2-2023::7.3.3Measure the impact of perturbations formally
iso-iec-24029-2-2023::7.4Check the effect of numerical accuracy at deployment
iso-iec-24029-2-2023::7.5.2Monitor robustness against the planned domain of operation
iso-iec-24029-2-2023::7.5.3Assess changes in robustness when the network keeps learning

What is ISO/IEC 24029-2:2023 and who does it apply to?

ISO/IEC 24029-2:2023 is a compliance framework from International with 3 domains and 18 controls. ISO/IEC's methodology for proving the robustness of neural networks with formal methods: define the domain by bounded attributes, express stability, sensitivity, relevance and reachability criteria, choose solvers, abstract interpretation, reachability analysis or model checking to fit the network, and apply them from design through verification, deployment and operation. It is used by organisations to establish and maintain compliance with industry standards and regulatory requirements.

What does ISO/IEC 24029-2:2023 actually require?

ISO/IEC 24029-2:2023 has 18 controls organised across 3 domains. The largest domains are Clause 5: Robustness properties and criteria (domain, stability, sensitivity, relevance, reachability) – ISO/IEC 24029-2:2023 (8 controls), Clause 7: Robustness assessment through the AI system life cycle – ISO/IEC 24029-2:2023 (7 controls), Clause 6: Choosing formal methods that fit the network and its data – ISO/IEC 24029-2:2023 (3 controls). Each control defines specific requirements that organisations must implement to achieve compliance.

If I already comply with another framework, how much of ISO/IEC 24029-2:2023 do I already cover?

ISO/IEC 24029-2:2023 does not currently have cross-framework mappings in our system. Check back as we continuously expand our mapping database.

How do I implement ISO/IEC 24029-2:2023?

Start your ISO/IEC 24029-2:2023 compliance journey by running a self-assessment on our platform to identify your current compliance posture. Our AI advisory can answer specific questions about ISO/IEC 24029-2:2023 requirements, and cross-framework mapping helps you leverage existing controls from other frameworks you may already comply with. Create a free account to access all 18 controls and track your progress.

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