Threat Modeling for Modern Systems: AI, IoT, and Cloud Security

Traditional security boundaries are disappearing as AI, IoT, and cloud-native systems become standard. To protect modern infrastructure, security professionals and developers must evolve their approach to identifying vulnerabilities before they can be exploited. This text-based course guides you from the fundamental principles of threat modeling to practical application in modern technology landscapes. You will learn how to systematically analyze systems, pinpoint architectural weaknesses, and design robust countermeasures for cutting-edge deployments. What you'll learn: - Understand foundational threat modeling methodologies like STRIDE and PASTA; - Analyze security risks unique to AI integrations, including data poisoning and model manipulation; - Evaluate IoT and network deployment architectures for hardware and protocol-level vulnerabilities; - Apply zero-trust principles to cloud-native applications and microservices; - Document and prioritize threats using structured, text-based modeling frameworks; - Design actionable mitigation strategies to secure modern software ecosystems. You will start by mastering core security definitions and classic threat modeling frameworks. From there, the text guides you through practical scenarios, showing you how to adapt these frameworks to modern cloud, IoT, and AI-driven environments. This course is designed for beginner cybersecurity enthusiasts, software developers, and system architects who want to build a strong foundation in modern threat analysis. No prior threat modeling experience is required. Start reading today to build more resilient, secure-by-design systems.