The Guidelines for Secure AI System Development have been jointly issued by the US Cybersecurity and Infrastructure Security Agency (CISA), the UK National Cyber Security Centre (NCSC), and their partners. These guidelines address the convergence of artificial intelligence (AI), cybersecurity, and critical infrastructure, emphasizing the importance of implementing Secure by Design principles.
Aligned with the U.S. Voluntary Commitments to Ensuring Safe, Secure, and Trustworthy AI, the guidelines advocate for customer ownership of security outcomes, radical transparency, accountability, and organizational structures prioritizing secure design.
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CISA and NCSC state that adherence to these guidelines will assist providers in constructing AI systems that operate as intended, are available when required, and function without exposing sensitive data to unauthorized entities.
Key Aspects of the Guidelines for Secure AI System Development:
New security vulnerabilities specific to AI systems are highlighted alongside conventional cybersecurity risks. Given the rapid evolution of AI, security considerations are often overlooked in favor of other aspects.
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The guidelines are structured across four primary areas within the AI system development life cycle: secure design, secure development, secure deployment, and secure operation and maintenance.
Secure Design:
In the initial phase of designing your AI system, it’s crucial to raise staff awareness about potential threats and risks. Take the time to model the threats specific to your system and ensure that security is a foundational consideration, striking a balance between functionality and performance. Additionally, when choosing AI models, carefully weigh the security benefits and trade-offs involved.
Secure Development:
Moving to the development stage, securing your supply chain becomes paramount. Identify, track, and protect your valuable assets throughout the process. Thoroughly document your data, models, and prompts, and actively manage any technical debt that may accrue.
Secure Deployment:
As you deploy your AI system, focus on securing the infrastructure supporting it. Implement continuous protection measures for your model, and establish robust incident management procedures. When releasing AI, do so responsibly, ensuring that user-friendly actions are facilitated to promote safe and effective utilization.
Secure Operation and Maintenance:
In the ongoing operation and maintenance phase, diligently monitor your system’s behavior and inputs. Embrace a secure-by-design approach to updates, and actively collect and share lessons learned to enhance the overall security and functionality of your AI system.
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CISA strongly recommends that stakeholders, including data scientists, developers, managers, decision-makers, and risk owners, review this guidance to inform their decisions on the development, implementation, and management of machine learning artificial intelligence systems.
Below is a copy detailing the guidelines:
Guidelines for secure AI system development
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