Publication Peer Review

The integration of LLMs and Generative AI introduces vital security considerations across development and deployment processes. Key responsibilities in this domain include secure coding practices, prompt injection defense, comprehensive output evaluation, operational qualification, and rigorous access control measures. Ensuring secure AI applications involves adopting robust security assessments, automated testing in CI/CD pipelines, and role-based access controls. Compliance with established frameworks such as the NIST AI Risk Management Framework and GDPR further reinforces organizational responsibility. Together, these practices support secure, ethical, and effective AI deployments.