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Framework for managing security risk in the LLM supply chain. π
In the evolving landscape of AI, securing the supply chain for Large Language Models (hashtag#LLMs) is more critical than ever. The WDTA AI-STR-03 standard lays the foundation for managing security risks across the entire LLM lifecycle β from development and training to deployment and maintenance.
This comprehensive framework addresses the unique challenges posed by AI integration into modern ecosystems. At its core, the AI-STR-03 standard adopts a multi-layered security approach, ensuring protection across network, system, platform, model, and data layers.
Key concepts include:
β Machine Learning Bill of Materials (ML-BOM) for transparent model development
β Zero Trust Architecture to safeguard system interactions
β Continuous monitoring & auditing to maintain security over time
By emphasizing these principles, the WDTA AI-STR-03 standard ensures the integrity, availability, confidentiality, controllability, and reliability of LLM systems throughout their supply chain.
Get access to the framework here, https://lnkd.in/gSHmGptx
βAt Precize Inc, we establish clear guidelines for application, model, and data set ownership, ensuring compliance with regulatory requirements, and implementing robust security measures, so organizations can effectively govern their cloud assets to mitigate risks, ensure accountability, and maximize the value derived from AI technologies.
βWorld Digital Technology Academy (WDTA) is a non-governmental organization (NGO) operating under the United Nations framework, WDTA upholds the core principle of "Speed, Safety, Sharingβ.
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