ISO/IEC 42005:2025 — AI System Impact Assessment
An international standard outlining methodology for conducting comprehensive impact assessments on AI deployments.

THE TECHNICAL LANGUAGE OF DIGITAL B2B INFRASTRUCTURE
A technical report outlining factors, threats, and architectural considerations influencing trustworthiness in artificial intelligence systems.
Understanding trustworthiness vulnerabilities helps enterprises anticipate safety incidents, defend against adversarial threats, and build stakeholder trust in automated decisions.
A financial institution conducts a threat assessment on a fraud detection system against ISO/IEC 24028 trustworthiness characteristics, identifying vulnerabilities to evasion attacks and dataset shift.
The standard provides an informational overview of trustworthiness factors and vulnerabilities, but does not specify certifiable requirements or testing methodologies.
The document explores key trustworthiness characteristics, including reliability, availability, resilience, robustness, safety, explainability, transparency, privacy, and fairness. It categorizes vulnerabilities and threats such as data poisoning, adversarial manipulation, model evasion, and bias, offering architectural mitigation approaches.
Cybersecurity, Systems Architecture
ISO — ISO/IEC 24028:2020 — https://www.iso.org/standard/77608.html
An international standard outlining methodology for conducting comprehensive impact assessments on AI deployments.
Standards establishing formal and empirical methodologies to assess the robustness of deep neural networks against perturbations.
International guidance on applying risk management principles specifically to artificial intelligence system lifecycles.
An international standard providing methodologies for assessing the impacts of artificial intelligence systems on individuals and society.
An international standard offering principles, a structured framework, and processes for enterprise risk management.