Cloud 101CircleEventsBlog
Save the date for CSA's 2024 Cyber Monday Sale: Get 50% off the exam token bundle!

Download Publication

AI Organizational Responsibilities - Core Security Responsibilities - Korean Translation
AI Organizational Responsibilities - Core Security Responsibilities - Korean Translation

AI Organizational Responsibilities - Core Security Responsibilities - Korean Translation

Release Date: 09/24/2024

This localized version of this publication was produced from the original source material through the efforts of chapters and volunteers but the translated content falls outside of the CSA Research Lifecycle. For any questions and feedback, contact [email protected]."

Here's the description from the original artifact publication page you would then include:

"This publication from the CSA AI Organizational Responsibilities Working Group provides a blueprint for enterprises to fulfill their core information security responsibilities pertaining to the development and deployment of Artificial Intelligence (AI) and Machine Learning (ML). Expert-recommended best practices and standards, including NIST AI RMF, NIST SSDF, NIST 800-53, and CSA CCM, are synthesized into 3 core security areas: data protection mechanisms, model security, and vulnerability management. Each responsibility is analyzed using quantifiable evaluation criteria, the RACI model for role definitions, high-level implementation strategies, continuous monitoring and reporting mechanisms, access control mapping, and adherence to foundational guardrails.
Key Takeaways:
  • The components of the AI Shared Responsibility Model
  • How to ensure the security and privacy of AI training data
  • The significance of AI model security, including access controls, secure runtime environments, vulnerability and patch management, and MLOps pipeline security
  • The significance of AI vulnerability management, including AI/ML asset inventory, continuous vulnerability scanning, risk-based prioritization, and remediation tracking

The other two publications in this series discuss the AI regulatory environment and a benchmarking model for AI resilience. By outlining recommendations across these key areas of security and compliance in 3 targeted publications, this series guides enterprises to fulfill their obligations for responsible and secure AI development and deployment.
 
Download this Resource

Prefer to access this resource without an account? Download it now.

Bookmark
Share
Related resources
AI Risk Management: Thinking Beyond Regulatory Boundaries
AI Risk Management: Thinking Beyond Regulatory ...
AI Organizational Responsibilities - Governance, Risk Management, Compliance and Cultural Aspects
AI Organizational Responsibilities - Governance...
AI in Medical Research: Applications & Considerations
AI in Medical Research: Applications & Consider...
How AI Changes End-User Experience Optimization and Can Reinvent IT
How AI Changes End-User Experience Optimization and Can Reinvent IT
Published: 11/15/2024
The Rocky Path of Managing AI Security Risks in IT Infrastructure
The Rocky Path of Managing AI Security Risks in IT Infrastructure
Published: 11/15/2024
ConfusedPilot: UT Austin & Symmetry Systems Uncover Novel Attack on RAG-based AI Systems
ConfusedPilot: UT Austin & Symmetry Systems Uncover Novel Attack on...
Published: 11/12/2024
The EU AI Act Comes Into Force: How This Pioneering Legislation Impacts Your Organization
The EU AI Act Comes Into Force: How This Pioneering Legislation Imp...
Published: 11/12/2024
Virtual Zero Trust Summit 2024
Virtual Zero Trust Summit 2024
November 20 | Virtual
Cloudbytes Webinar Series
Cloudbytes Webinar Series
January 1 | Online
Are you a research volunteer? Request to have your profile displayed on the website here.

Interested in helping develop research with CSA?

Related Certificates & Training