AI Cybersecurity: Attack and Defend

This course explores the intersection of AI and cybersecurity, starting with a foundational understanding of AI technologies such as machine learning, deep learning, and natural language processing, as well as their applications in various industries. The content delves into mitigating risks associated with AI adoption, including risk management and ethical considerations, and identifying vulnerabilities in AI systems. The importance of integrating AI into security operations is covered through the use of AI for intrusion detection, threat intelligence, and automated incident response, as well as AI’s potential for transforming hacking techniques while highlighting AI-powered attacks and tools.  The Course also emphasizes the need for aligning AI with common security frameworks and regulatory compliance, as well as exploring future trends such as federated learning, AI-powered cyber deception, quantum computing for AI, explainable AI, and AI-driven security automation.  AI and Cyber: Attack and Defend Benefits Training Prerequisites Attendees should have foundational knowledge in networking and cybersecurity. AI Cybersecurity Training Outline Chapter 1: Architecture and Operation of AI What is AI?  Evolution of AI technology  Machine learning, deep learning, natural language processing  GenAI  Algorithms, data sets, and models  AI as a service (AIaaS)  Applying AI in Security  Why need Cybersecurity in GenAI projects  LAB: Google Vision, DLP Chapter 2: Risk in Adopting AI Solutions Identifying and managing risks of AI implementations  Ethical considerations  Security controls for AI  Protecting from GenAI-aided attacks  LAB: Google Gemini and ChatGPT  Chapter 3: Hacking AI Vulnerabilities Typical attack vectors against AI systems  Vulnerabilities in AI algorithms and models  AI Red teaming  Exploiting AI weaknesses for malicious gain  Cyberattacks/incidents related to the use of GenAI  LAB: OWASP Top 10 Machine Learning Security Risks  Chapter 4: Exploiting AI to Hack Systems Transforming Hacking Techniques with AI  New Attack Vectors  How GenAI is being used for cybercrime     AI-powered hacking tools  Case studies of successful AI-based attacks  LAB: Set up ChatGPT for Hacking  Chapter 5: Improving Security Operations with AI Integrating AI in security and IT operations  AI in intrusion detection and threat intelligence  AI-powered security information and event management (SIEM)  Using AI for Automated Incident Response  Microsoft Security Copilot   LAB: Google Chronicle SOAR War Story  Chapter 6: Common AI Security Frameworks Regulatory and compliance issues related to AI  Securing AI in cloud environments  NIST AI Risk Management Framework  ISO/IEC 27050-2  AI Incident Taxonomy for Adversarial Events  Chapter 7: Evolving AI security Federated Learning  AI-Powered Cyber Deception  Quantum Computing for AI  Explainable AI  AI-Driven Security Automation