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Mapping of the UK NCSC /CISA [Joint Guidelines for secure AI system development](https://www.ncsc.gov.uk/collection/guidelines-secure-ai-system-development) to the controls here at the AI Exchange.
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To see those controls linked to threats, refer to the [Periodic table of AI security](/goto/periodictable/).
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To see those controls linked to threats, refer to the [Periodic table of AI security](/goto/periodictable/).
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Note that the UK Government drove an initiative through their DSIT repartment to build on these joint guidelines and produce the [DSIT Code of Practice for the Cyber Secyrity of AI](https://www.gov.uk/government/publications/ai-cyber-security-code-of-practice/code-of-practice-for-the-cyber-security-of-ai#code-of-practice-principles), which reorganizes things according to 13 principles, does a few tweaks, and adds a bit more governance. The principle mapping is added below, and adds mostly post-market aspects:
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- Principle 10: Communication and processes assoiated with end-users and affected entities
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- Principle 13: Ensure proper data and model disposal
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1. Secure design
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- Raise staff awareness of threats and risks:
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- Raise staff awareness of threats and risks (DSIT principle 1):
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#[SECURITY EDUCATE](/goto/seceducate/)
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- Model the threats to your system:
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- Model the threats to your system (DSIT principle 3):
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See Risk analysis under #[SECURITY PROGRAM](/goto/secprogram/)
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- Design your system for security as well as functionality and performance:
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- Design your system for security as well as functionality and performance (DSIT principle 2):
- Consider security benefits and trade-offs when selecting your AI model
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All development-time data science controls (currently 13), #[EXPLAINABILITY](/goto/explainability/)
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2. Secure Development
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- Secure your supply chain:
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- Secure your supply chain (DSIT principle 7):
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#[SUPPLY CHAIN MANAGE](/goto/supplychainmanage/)
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- Identify, track and protect your assets:
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- Identify, track and protect your assets (DSIT principle 5):
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#[DEVELOPMENT SECURITY](/goto/devsecurity/), #[SEGREGATE DATA](/goto/segregatedata/), #[CONFIDENTIAL COMPUTE](/goto/confcompute/), #[MODEL INPUT CONFIDENTIALITY](/goto/modelinputconfidentiality/), #[RUNTIME MODEL CONFIDENTIALITY](/goto/runtimemodelconfidentiality/), #[DATA MINIMIZE](/goto/dataminimize/), #[ALLOWED DATA](/goto/alloweddata/), #[SHORT RETAIN](/goto/shortretain/), #[OBFUSCATE TRAINING DATA](/goto/obfuscatetrainingdata/) and part of #[SECURITY PROGRAM](/goto/secprogram/)
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- Document your data, models and prompts:
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- Document your data, models and prompts (DSIT principle 8):
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Part of #[DEVELOPMENT PROGRAM](/goto/devprogram/)
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- Manage your technical debt:
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Part of #[DEVELOPMENT PROGRAM](/goto/devprogram/)
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3. Secure deployment
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- Secure your infrastructure:
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- Secure your infrastructure (DSIT principle 6):
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Part of #[SECURITY PROGRAM](/goto/secprogram/) and see ‘Identify, track and protect your assets’
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- Protect your model continuously:
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#[INPUT DISTORTION](/goto/inputdistortion/), #[FILTER SENSITIVE MODEL OUTPUT](/goto/filtersensitivemodeloutput/), #[RUNTIME MODEL IO INTEGRITY](/goto/runtimemodeliointegrity/), #[MODEL INPUT CONFIDENTIALITY](/goto/modelinputconfidentiality/), #[PROMPT INPUT VALIDATION](/goto/promptinputvalidation/), #[INPUT SEGREGATION](/goto/inputsegregation/)
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- Develop incident management procedures:
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Part of #[SECURITY PROGRAM](/goto/secprogram/)
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- Release AI responsibly:
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Part of #[DEVELOPMENT PROGRAM](/goto/devprogram/)
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- Make it easy for users to do the right things:
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Part of #[SECURITY PROGRAM](/goto/secprogram/)
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- Make it easy for users to do the right things (DSIT principe 4, called Enable human responsibility for AI systems):
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Part of #[SECURITY PROGRAM](/goto/secprogram/), and also involving #[EXPLAINABILITY](/goto/explainability/), documenting prohibited use cases, and #[HUMAN OVERSIGHT](/goto/humanoversight))
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4. Secure operation and maintenance
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- Monitor your system’s behaviour:
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- Monitor your system’s behaviour (DSIT principle 12 and similar to DSIT principle 9 - appropriate testing and validation):
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