• AI practitioners and researchers looking to deepen their understanding of Generative AI security.
• Cybersecurity professionals aiming to integrate AI into their security practices.
• Tech enthusiasts interested in the implications of Generative AI on security and privacy.

• No coding experience required; suitable for beginners

Course Outline:

Module 1: Introduction to Generative AI

• Explore the fundamental principles of Generative AI (GANs, VAEs, etc.)
• Understand the different types of Gen AI models and their capabilities.
• Discuss the various applications of Gen AI across industries.

Module 2: Security Landscape of Gen AI

• Identify potential security threats associated with Gen AI, such as deep-fakes, synthetic data poisoning, and adversarial attacks.
• Learn about techniques used to manipulate and exploit Gen AI models for malicious purposes.
• Analyse the impact of Gen AI on data privacy and security.

Module 3: Mitigating Gen AI Security Risks

• Explore best practices for securing Gen AI development pipelines.
• Discuss techniques for data sanitization and adversarial training to improve model robustness.
• Analyze methods for detecting and preventing Gen AI-based attacks.
• Learn about responsible AI development principles for secure Gen AI applications.

Module 4: Case Studies and Applications

• Analyze real-world case studies of Gen AI security breaches and vulnerabilities.
• Explore how organizations can leverage Gen AI for security applications like anomaly detection and threat analysis.
• Discuss the future of Gen AI security and emerging solutions.