Learn about certification frameworks and evaluation criteria for secure and resilient AI. This section explains what stakeholders need to know to check if AI systems are safe and work well, based on certain rules.

ETSI deliverableTitleStatus
ETSI TR 104 030 V1.1.1 (2025-03)​Securing Artificial Intelligence (SAI); Critical Security Controls for Effective Cyber Defence; Artificial Intelligence Sector​Published
ETSI TS 104 050 V1.1.1 (2025-03)​Securing Artificial Intelligence (SAI); AI Threat Ontology and definitions​Published
ETSI TS 104 224 V1.1.1 (2025-03)​Securing Artificial Intelligence (SAI); Explicability and transparency of AI processing​Published
ETSI TR 104 048 V1.1.1 (2025-01)​Securing Artificial Intelligence (SAI); Data Supply Chain Security​Published
ETSI TR 104 222 V1.2.1 (2024-07)​Securing Artificial Intelligence; Mitigation Strategy Report​Published
ETSI TR 104 066 V1.1.1 (2024-07)​Securing Artificial Intelligence; Security Testing of AI ​Published
ETSI TR 104 062 V1.2.1 (2024-07)​Securing Artificial Intelligence; Automated Manipulation of Multimedia Identity Representations​Published
ETSI TR 104 225 V1.1.1 (2024-04)​Securing Artificial Intelligence TC (SAI); Privacy aspects of AI/ML systems​Published
ETSI TR 104 067 V1.1.1 (2024-04)​Securing Artificial Intelligence (SAI); Proofs of Concepts Framework​Published
ETSI TR 104 032 V1.1.1 (2024-02)​Securing Artificial Intelligence (SAI); Traceability of AI Models​Published
ETSI TR 104 031 V1.1.1 (2024-02)​Securing Artificial Intelligence (SAI); Collaborative Artificial Intelligence​Published
StandardTitleDescription
ISO/IEC 42001​Artificial Intelligence Management SystemSpecifies requirements for AI managements systems within an organization.
ISO/IEC 22989​Artificial Intelligenece Concepts and TerminologyProvides a comprehensive framework for understanding AI concepts and terminology.
ISO/IEC 23894​Guidance on risk management for AIOffers guidelines for identifying, assessing, and mitigating risks associated with AI systems.
ISO/IEC 5338​AI system life cycle processesProvides a framework for managing AI systems throughout their lifecycle.
ISO/IEC 42005​AI system impact assessmentOutlines the methodology for assessing the impact of AI systems.
ISO/IEC TR 24029-1:2021​Assessment of the robustness of neural networks – Part 1: OverviewProvides an overview of assessing the robustness of neural networks to ensure security and reliability.