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Secure AI: Threat Model & Test Endpoints · LearnSpace
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courseraIT и технологии

Secure AI: Threat Model & Test Endpoints

Курс от Coursera
Средний≈ 4.8 чАнглийский
О курсеНавыкиПрограммаПреподаватели

О курсе

Master the critical skills needed to secure AI inference endpoints against emerging threats in this comprehensive intermediate-level course. As AI systems become integral to business operations, understanding their unique vulnerabilities is essential for security professionals. You'll learn to identify and evaluate AI-specific attack vectors including prompt injection, model extraction, and data poisoning through hands-on labs and real-world scenarios. Design comprehensive threat models using STRIDE and MITRE ATLAS frameworks specifically adapted for machine learning systems. Create automated security test suites covering unit tests for input validation, integration tests for end-to-end security, and adversarial robustness testing. Implement these security measures within CI/CD pipelines to ensure continuous validation and monitoring. Through practical exercises with Python, GitHub Actions, and monitoring tools, you'll gain experience securing production AI deployments. Perfect for developers, security engineers, and DevOps professionals ready to specialize in the rapidly growing field of AI security. This course is designed for developers, security engineers, and DevOps professionals looking to specialize in AI security. With a solid understanding of Python, APIs, and CI/CD concepts, you'll dive deep into securing AI inference endpoints against emerging threats like prompt injection and data poisoning. Through hands-on labs, you'll learn to design threat models, create automated security tests, and integrate continuous security measures into CI/CD pipelines. Perfect for those eager to enhance their expertise in safeguarding AI systems. A basic knowledge of Python, APIs, web services, and CI/CD concepts is essential for this course. Python will help with scripting, while understanding APIs and CI/CD will enable you to automate and manage deployments effectively. These skills are key to successfully navigating the course. By the end of this course, you'll have the skills to automate and secure your development workflows, leveraging tools like Bitbucket Pipelines. You'll be ready to apply industry best practices to integrate, test, and deploy applications seamlessly, enhancing both efficiency and security in your DevOps processes.

Навыки, которые вы освоите

Security TestingThreat ModelingAI SecurityUnit TestingEvent MonitoringMITRE ATT&CK FrameworkContinuous IntegrationCI/CDDevSecOpsScriptingEndpoint SecurityDevOpsContinuous MonitoringApplication SecuritySystem MonitoringData ValidationIntegration TestingTest Script DevelopmentAPI Testing

Программа курса

3 модулей · 23 учебных материалов

01Understanding AI-Specific Threat Models8 материалов

Lesson 1: Understanding AI-Specific Threat Models

Investigate Security Breach: TechCorp's AI Vulnerability CrisisDIALOGUEWelcome to the Course: Course OverviewЧтениеWelcome to AI Security: The New FrontierВидеоTraditional vs AI-Specific Attack SurfacesВидео

Учитесь у экспертов

Starweaver

Global Leaders in Professional & Technology Education

Ritesh Vajariya

Advisor | Leader | Speaker |Author

Secure AI: Threat Model & Test Endpoints
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Обучение откроется на Coursera
в новой вкладке

Обучение на Coursera

≈ 4.8 ч

3 модулей

Язык: Английский

Субтитры: Арабский, Французский, Итальянский, Бразильский португальский, Корейский, Немецкий, Индонезийский, Испанский, Японский

Часть программы вашего университета
AI Attack Vectors: Prompt Injection and Model ExtractionВидео
Building AI Threat Models with STRIDE and MITRE ATLASВидео
Hands-On-Learning: Analyze Threat Model: SecureBank's LLM Infrastructure Взаимная проверка
MITRE ATLAS: Adversarial Threat Landscape for AI SystemsЧтение
02Creating Security Test Cases for AI Systems6 материалов

Lesson 2: Creating Security Test Cases for AI Systems

Design Test Strategy: HealthAI's Medical Diagnosis SystemDIALOGUEUnit Testing for AI Input Validation and SanitizationВидеоOWASP Testing Guide for LLM ApplicationsЧтениеIntegration Testing for End-to-End AI SecurityВидеоAdversarial Testing and Robustness EvaluationВидеоHands-On-Learning: Design Adversarial Test Suite: MediScan's Diagnostic AIВзаимная проверка
03CI/CD Integration and Continuous Security9 материалов

Lesson 3: CI/CD Integration and Continuous Security

Optimize Pipeline: StreamAI's Real-Time Translation ServiceDIALOGUECI/CD Fundamentals for AI Security AutomationВидеоImplementing Security Gates and Quality ChecksВидеоMLOps Security Best Practices GuideЧтениеContinuous Monitoring and Incident ResponseВидеоHands-On-Learning: Implement CI/CD Pipeline: GlobalFinance's Trading AlgorithmВзаимная проверкаYour AI Security Journey: Next StepsВидеоProject: Comprehensive AI Security Audit: HealthTech AI Diagnostic Platform Взаимная проверкаAI Security Comprehensive AssessmentЗадание