The Cloud Security Alliance (CSA) provides comprehensive guidelines on data security within AI environments, emphasizing a lifecycle approach to protect sensitive training data, models, and inference inputs from threats like data poisoning, theft, and supply chain vulnerabilities. Key recommendations include conducting thorough risk assessments to identify and prioritize AI-specific security risks, followed by implementing controls such as access management, encryption, and continuous monitoring across stages from planning and development to deployment, operations, and decommissioning. The CSA’s AI Controls Matrix (AICM) further supports this with 18 security domains, including dedicated data security and privacy objectives, alongside tools like Valid-AI-ted for assessments, ensuring AI systems are secure by design in cloud-native settings.
Publication's URL
https://cloudsecurityalliance.org/artifacts/data-security-within-ai-environmentsAdditional documents on this topic
- OWASP Practical Guide for Secure MCP Server Development
- NIST IR 8596 Cybersecurity Framework Profile for Artificial Intelligence (Cyber AI Profile): NIST Community Profile ★★★★★
- ETSI EN 304 223: Securing Artificial Intelligence (SAI) – Baseline Cyber Security Requirements for AI Models and Systems
- CISA Principles for the Secure Integration of Artificial Intelligence in Operational Technology
- OWASP AI Testing Guide ★★★★★