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Learn how to secure AI and LLM-based applications deployed in public cloud environments through Fortinet's comprehensive security framework in this 23-minute conference presentation. Discover why the cloud's scalability, GPU access, and managed services make it the ideal platform for AI development, while simultaneously creating new security challenges that require architectural changes to traditional security approaches. Explore the growing threat landscape facing cloud AI applications, including model theft, prompt injection attacks, misconfigurations, and credential theft that organizations are increasingly reporting. Master Fortinet's layered security strategy that combines FortiOS for zero-trust access and continuous posture assessment, FortiCNAP for vulnerability scanning throughout the AI workload lifecycle, and FortiWeb for web application and API protection using machine learning to detect anomalous activities and sanitize LLM user input. Understand how to address the OWASP Top 10 threats to LLMs while implementing robust data protection measures including data leak prevention on endpoints and in-line controls for sensitive training data access. Examine a practical demo environment featuring segmented networks with comprehensive security measures, including north-south and east-west traffic inspection between nodes, and witness how traditional attacks like SQL injection can escalate into SSRF and model corruption to compromise AI applications.
