Cybersecurity Defense with GenAI: Foundations & Fundamentals

Driving Enterprise GenAI Adoption: Tools, Frameworks, and Real-World Case Studies from Industry Leaders

Created by: Sivaram A
AI Strategy / AI Solution Architect

Created by: Gayathri B R
Cybersecurity Consulting/ Responsible AI Adoption

What Will I Learn?

• Master the foundational principles and best practices for integrating Generative AI in cybersecurity.
• Become aware about AI, ML, and deep learning, focusing on their applications in various industries, including a case study on Tesla Autopilot.
• Study the intersection of AI/ML and cybersecurity, understanding ethical considerations and potential risks with examples from real-world scenarios.
• Explore the latest trends as per industry reports like those from Gartner.
• Delve into typical cloud-based and AI-specific cybersecurity architectures, learning how they differ and why they're essential.
• Develop strategies for managing AI data privacy, including data quality, governance, and lifecycle management.
• Learn about AI risk management frameworks like NIST AI RMF, and explore case studies on navigating AI risks.
• Understand key AI controls and policies, including the CIA Triad, OWASP AI vulnerabilities, and AI governance frameworks.
• Gain knowledge about auditing AI systems, understanding components of compliance, and readiness comparisons.
• Explore various AI regulatory frameworks, including the EU AI Act, GDPR, and ethical AI frameworks by OECD.
• Understand the security implications of Generative AI, exploring defenses, future challenges, and opportunities.
• Learn about innovative GenAI solutions and opportunities, including custom LLM implementations and industry-specific applications.
• Understand how AI can be used to enhance governance practices and develop frameworks for low-risk AI adoption.
• Study key controversies and ethical issues in AI, as outlined by UNESCO and other bodies, to inform responsible AI practices.

Requirements

• Basic understanding of AI/ML tech is required
• A keen interest in staying updated on the latest developments in the world of AI
• Basic Awareness and Knowledge of AI Use Cases

Target audience

• Product Managers: Ideal for those adopting LLM-based solutions, this course will help you enhance product development and ensure secure implementation.
• Data Scientists: Perfect for professionals aiming to integrate GenAI with data-driven projects, manage biases, and mitigate security risks effectively.
• Cybersecurity Teams: Essential for cybersecurity and CISO teams involved in AI/ML and GenAI adoption, focusing on securing AI initiatives and understanding emerging threats.
• Business Leaders and Executives: Beneficial for business leaders and executives targeting GenAI-based use case adoption, driving innovation while maintaining compliance and security.
• Innovative Problem Solvers: Suited for creative thinkers who enjoy tackling complex challenges with cutting-edge technology and AI-driven solutions.
• IT Professionals: Crucial for IT experts responsible for managing and securing AI infrastructure, ensuring robust cybersecurity measures are in place.
• AI Enthusiasts and Tech Innovators: Great for individuals passionate about AI, looking to stay updated with the latest trends and advancements in Generative AI and cybersecurity.
• Compliance Officers and Legal Experts: Valuable for professionals overseeing compliance and regulatory aspects, providing insights into AI frameworks, policies, and ethical considerations.