Course Topics / Agenda
Please note that this list of topics is based on our standard course offering, evolved from typical industry uses and trends. We’ll work with you to tune this course and level of coverage to target the skills you need most. Topics, agenda and labs are subject to change, and may adjust during live delivery based on audience skill level, interests and participation.
- Introduction to AI in Security
- Understand the role of AI in the field of cybersecurity and the evolution of threats.
- The basics of AI and its relevance to security
- Cybersecurity landscape: traditional threats vs. AI-enabled threats
- Real world examples of AI in security
- Understanding the role of AI in Threat Intelligence
- Lab: Simulating AI-driven threat analysis using open-source threat intelligence tools
- Playing Detective: Identifying AI Threats and Vulnerabilities
- Grasp the inherent threats and vulnerabilities of AI systems
- Understanding the different types of AI threats
- Learning about common AI vulnerabilities
- Exploring case studies of major AI-based security breaches
- AI and data privacy concerns
- Lab: Identifying vulnerabilities in an AI system (2:30 – 4:00)
- Tools Used in Lab: Python, Scikit-learn, OWASP Dependency-Check
- Building the AI Fortress: Defense Mechanisms 101
- Gain knowledge on how to safeguard AI systems from security threats.
- Importance of AI Security Measures
- Learning about AI Defense Mechanisms
- AI in intrusion detection and prevention systems • AI in risk assessment and vulnerability management
- Lab: Designing a basic AI-driven Intrusion Detection System
- CSI Cyber: A Foray into AI Forensics
- Understand how forensic techniques are applied in AI security.
- The role of forensics in AI Security
- Basics of AI Forensic Analysis
- Case studies of forensic analysis in AI security incidents
- AI in forensic data analysis
- Lab: Conducting a simple forensic analysis on an AI system
- Crisis Averted: Crafting Your AI Incident Response Plan
- Learn how to respond to incidents in AI systems effectively.
- Basics of Incident Response (IR) in AI systems
- AI in IR: Automated and adaptive response
- Designing an incident response plan for AI systems
- Lab: Creating a mock incident response plan for an AI system
- What’s Next? Preparing for Future AI Security Challenges
- Get insights into the future trends of AI in cybersecurity.
- Future threats: Deepfakes, autonomous weapons, etc.
- AI in quantum computing security
- AI-driven Security Orchestration, Automation, and Response (SOAR)
- The role of AI in zero-trust architectures
- Lab: Simulating the detection of a deepfake
Course Wrap
- Next steps in becoming an AI Security Expert
Learning Objectives
Throughout the course you’ll:
- Gain a clear understanding of AI and its integral role in the realm of cybersecurity, providing a solid foundation for the rest of the course.
- Learn to identify and understand various types of AI threats and vulnerabilities, improving your ability to predict and mitigate potential risks.
- Acquire the knowledge to design and implement robust AI defense mechanisms and AI Driven Intrusion Systems (IDS), equipping you to safeguard your systems effectively.
- Delve into the fascinating world of AI forensics and learn how to conduct basic forensic analyses on AI systems.
- Master the art of creating and executing incident response plans for AI systems, a vital skill for any security professional.
- Learn specific techniques to detect deepfakes and understand their potential security implications, equipping you to counter one of the emerging threats in the AI security landscape.
- Get hands-on experience with innovative open-source tools such as Python, Scikit-learn, and Suricata IDS, enhancing your ability to use these tools effectively in AI security.
- Get insights into future trends in AI security, ensuring that you’re well-prepared for what’s around the corner in this rapidly evolving field.
To ensure a smooth learning experience and maximize the benefits of attending this course, you should have the following prerequisite skills:
- A foundational understanding of artificial intelligence, including the basic principles, applications, and types of AI.
- Familiarity with basic cybersecurity principles, understanding of threats, defense mechanisms, and incident response.
- Basic Python programming skills and / or a general comfort with coding
- Basic knowledge of computer networks, systems, and how they interact
- Some basic experience in data analysis or basic statistical concepts.
Ten (10) business days’ notice is required to reschedule a class with no additional fees. Notify TOPTALENT LEARNING as soon as possible at 469-721-6100 or by written notification to info@toptalentlearning.com to avoid rescheduling penalties.
Please contact our team at 469-721-6100; we will gladly guide you through the online purchasing process.
You will receive a receipt and an enrollment confirmation sent to the email you submitted at purchase. Your enrollment email will have instructions on how to access the class. Any additional questions our team is here to support you. Please call us at 469-721-6100.
If a student is 15 minutes late, they risk losing their seat to a standby student. If a student is 30 minutes late or more, they will need to reschedule. A no-show fee will apply. Retakes are enrolled on a stand-by basis. The student must supply previously issued courseware. Additional fees may apply.
You will receive a ‘Certificate of Completion’ once you complete the class. If you purchased an exam voucher for the class, a team member from TOPTALENT LEARNING will reach out to discuss your readiness for the voucher and make arrangements to send it.
