New ETSI standard defines cybersecurity rules for AI systems
AI cybersecurity gains formal structure as ETSI introduces EN 304 223, with ETSI outlining security principles spanning design, deployment, maintenance and end of life.
ETSI has released ETSI EN 304 223, a new European Standard establishing baseline cybersecurity requirements for AI systems.
Approved by national standards bodies, the framework becomes the first globally applicable EN focused specifically on securing AI, extending its relevance beyond European markets.
The standard recognises that AI introduces security risks not found in traditional software. Threats such as data poisoning, indirect prompt injection and vulnerabilities linked to complex data management demand tailored defences instead of conventional approaches alone.
ETSI EN 304 223 combines established cybersecurity practices with targeted measures designed for the distinctive characteristics of AI models and systems.
Adopting a full lifecycle perspective, the ETSI framework defines thirteen principles across secure design, development, deployment, maintenance and end of life.
Alignment with internationally recognised AI lifecycle models supports interoperability and consistent implementation across existing regulatory and technical ecosystems.
ETSI EN 304 223 is intended for organisations across the AI supply chain, including vendors, integrators and operators, and covers systems based on deep neural networks, including generative AI.
Further guidance is expected through ETSI TR 104 159, which will focus on generative AI risks such as deepfakes, misinformation, confidentiality concerns and intellectual property protection.
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