Agentic AI - Masterclass sur le risque et la cybersécurité 2025

Aperçu

Learn the Cyber security risks around AI Agents and Agentic AI and how to mitigate them What you'll learn:

How Agentic AI Is A Game Changer For Risk And SecurityHow Agentic AI WorksWhat Are The Unique Risks That Agentic AI IntroducesHow To Mitigate Agentic AI RisksHow To Threat Model Agentic AI Systems Agentic AI represents the next evolution of artificial intelligence—systems that can autonomously make decisions, plan actions, and interact with the world with minimal human intervention. As AI becomes increasingly autonomous, new risks and security challenges emerge that go beyond traditional cybersecurity concerns.The "Agentic AI Risk and Cybersecurity Masterclass" is a comprehensive course designed to provide a deep understanding of agentic AI technologies, their unique risk landscape, and the best practices for securing these intelligent systems.This course explores the principles, components, and security considerations of Agentic AI, equipping you with the knowledge to assess, mitigate, and defend against emerging AI threats.What You Will LearnFundamental principles and architecture of Agentic AI systemsUnderstanding the risk landscape in autonomous AI and its implicationsSecurity threats unique to Agentic AI, including AI autonomy risks, adversarial manipulation, and decision-based attacksHow prompt injections and model exploitation attacks evolve in an Agentic AI contextStrategies for designing secure Agentic AI systems with ethical safeguards and risk mitigation controlsCompliance and governance frameworks for Agentic AI cybersecurityCourse OutlineIntroduction to Agentic AIWhat is Agentic AI?How does it differ from Generative AIWhy security in Agentic AI is criticalRisks in Agentic AIOverview of the Agentic AI risk landscapeThreat modeling Agentic AI systemsCase Study of Threat Modeling Agentic AIsystems Security in Agentic AICreating a Security Framework For Agentic AIThreat vectors and attack techniques against autonomous AIHijacking attacks, data poisoning, and malicious automationBest practices for hardening Agentic AI models and deploying AI security frameworksWho Should Take This CourseThis course is ideal for individuals looking to understand and mitigate the cybersecurity risks associated with autonomous AI systems, including:

AI engineers & researchersCybersecurity professionalsData Scientists & AI Ethics specialistsIT Managers & risk professionalsBusiness leaders exploring Agentic AI adoptionPre-requisites Basic understanding of AI and cybersecurity concepts is recommended, but no prior knowledge of Agentic AI is required.InstructorTaimur Ijlal is a multi-award-winning cybersecurity leader with over 20+ years of global experience in cyber risk management, AI security, and IT governance.

He has been recognized with industry accolades such as CISO of the Year, CISO Top 30, and Most Outstanding Security Team.Taimur’s cybersecurity and AI courses have thousands of students worldwide, and his work has been featured in ISACA Journal, CIO Magazine Middle East, and multiple AI security publications. His books on AI Security and Cloud Computing have ranked as #1 new releases on Amazon.Join this course to stay ahead of the rapidly evolving landscape of Agentic AI Risk and Cybersecurity!

Programme

• Introduction à l'IA Agentique
Qu'est-ce que l'IA Agentique ?
En quoi diffère-t-elle de l'IA Générative ?
Pourquoi la sécurité dans l'IA Agentique est-elle cruciale ?
• Risques dans l'IA Agentique
Aperçu du paysage des risques de l'IA Agentique
Modélisation des menaces des systèmes IA Agentiques
Étude de cas de la Modélisation des menaces des systèmes IA Agentiques
• Sécurité dans l'IA Agentique
Création d'un Cadre de Sécurité pour l'IA Agentique
Vecteurs de menace et techniques d'attaque contre l'IA autonome
Attaques de détournement
Empoisonnement des données
Automatisation malveillante
Meilleures pratiques pour renforcer les modèles IA Agentiques et déployer des cadres de sécurité de l'IA
• Compréhension du Paysage des Risques dans l'IA Autonome
Menaces uniques à la sécurité de l'IA Agentique
Risques liés à l'autonomie de l'IA
Manipulation adverse
Attaques basées sur les décisions
Comment les injections de promptes et les attaques d'exploitation de modèles évoluent dans un contexte IA Agentique
• Conception de Systèmes d'IA Agentique Sécurisés
Stratégies pour une conception sécurisée avec des sauvegardes éthiques
Contrôles d'atténuation des risques
Cadres de conformité et de gouvernance pour la cybersécurité de l'IA Agentique
• Conclusion
Tendances émergentes en termes de risques et cybersécurité de l'IA Agentique
Orientations futures et domaines de recherche dans la sécurisation des systèmes IA autonomes

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Enseigné par

Taimur Ijlal | Award winning cybersecurity leader and instructor

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Matières

Computer Science