How does Google Cloud ensure the security of AI models?

Google Cloud ensures the security of AI models primarily through the implementation of encryption, access controls, and regular audits. Encryption protects sensitive data at rest and in transit, thereby safeguarding it from unauthorized access and breaches. Access controls are critical as they determine who can interact with the AI models and what permissions they have, ensuring that only authorized personnel can make modifications or access the underlying data. Regular audits are important for monitoring compliance, assessing potential vulnerabilities, and ensuring that security measures are effective and up to date.

In contrast, relying solely on basic password protection lacks the robustness needed to secure complex AI systems, as passwords can be weak and easily compromised. Restricting access only to data scientists may limit collaboration and innovation, while also not being sufficient on its own to secure the models effectively. Limiting the number of users can provide some level of security, but it doesn't address the broader security framework needed to protect AI models comprehensively. Therefore, the systematic approach of encryption, access controls, and consistent auditing is crucial for maintaining security in AI models on Google Cloud.