AI System Security Compliance Standard

An AI System Security Compliance Standard is a security compliance standard that defines security requirements and control objectives for AI system development and AI system deployment.

• AKA: AI Security Standard, Machine Learning Security Compliance Standard, AI System Security Framework.
• Context:
  • It can typically specify AI Model Security Requirements including model encryption, model access control, and model integrity verification.
  • It can typically mandate AI Training Data Protection through data classification, data encryption, and data access logging.
  • It can typically require AI System Threat Modeling for adversarial attack mitigation.
  • It can typically define AI Supply Chain Security covering third-party components and pre-trained models.
  • It can typically establish AI Incident Response Procedures for security breach handling.
  • ...
  • It can often prescribe AI Explainability Requirements for security audit purposes.
  • It can often incorporate Privacy-Preserving AI Techniques like differential privacy and federated learning.
  • It can often address AI System Monitoring Requirements for anomaly detection.
  • It can often include AI Vulnerability Assessment through penetration testing and red team exercises.
  • ...
  • It can range from being a Basic AI System Security Compliance Standard to being a Comprehensive AI System Security Compliance Standard, depending on its security control coverage.
  • It can range from being a Industry-Specific AI System Security Compliance Standard to being a General-Purpose AI System Security Compliance Standard, depending on its application scope.
  • ...
  • It can complement ISO/IEC 27001 Standard with AI-specific security controls.
  • It can support SOC 2 Type II Compliance Framework through trust criteria mapping.
  • It can enable Zero-Trust AI System Security Architecture via architectural requirements.
  • It can inform AI System Regulatory Compliance Audit Processes with compliance checklists.
  • ...
• Example(s):
  • International AI System Security Compliance Standards, such as:
    • ISO/IEC 23053 AI Security Standard defining AI trustworthiness requirements.
    • IEEE P2986 AI Security Standard for AI data governance.
    • NIST AI Risk Management Framework providing AI security guidelines.
  • Industry AI System Security Compliance Standards, such as:
    • Healthcare AI Security Standard addressing medical AI privacy.
    • Financial Services AI Security Standard for algorithmic trading security.
    • Automotive AI Security Standard covering autonomous vehicle AI.
  • Regional AI System Security Compliance Standards, such as:
    • EU AI Security Requirements under EU AI Act.
    • Singapore Model AI Governance Framework for AI deployment security.
  • ...
• Counter-Example(s):
  • General IT Security Standard, which lacks AI-specific security considerations.
  • AI Ethics Standard, which focuses on ethical principles rather than security controls.
  • Data Quality Standard, which addresses data accuracy without security requirements.
• See: ISO/IEC 27001 Standard, AI System Data Governance Framework, AI Model Security Assessment, Adversarial Machine Learning Defense, Privacy-Preserving Machine Learning, AI System Vulnerability Management, Trustworthy AI Framework.

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