AI and Cyber Security: Attack and Defend

Duration: 3 days
Labs: Yes
Language: English
Level: Intermediate

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 Security: Attack and Defend Delivery Methods

In-Person
Online
Upskill your whole team by bringing Private Team Training to your facility.

AI and Cyber Security: Attack and Defend Course Information

In this course, you will:
- Explain the architecture and operation of AI technologies
- Assess the security, privacy, and ethical risks associated with adopting AI
- Identify and test vulnerabilities in AI systems
- Implement controls to secure and monitor AI systems
- Apply AI to strengthen cybersecurity operations and governance
Training Prerequisites

Attendees should have foundational knowledge in networking and cybersecurity.
Who should attend?
- Cybersecurity Professionals
- AI and Data Science Professionals
- IT Professionals
- Data Privacy and Compliance Officers
- Developers and Software Engineers

AI and Cyber Security: Attack and Defend Course Outline

Learning Objectives

Chapter 1: Architecture and Operation of AI

Evolution of AI technology
Applying AI in Security
Machine Learning
Deep Neural Networks
Federated Learning
CNN, RNN, RvNN, Transformers
NLP, LLM
Generative AI
LAB: Utilizing a Small Language Model

Chapter 2: Risk in Adopting AI

Risk in Security
Risks of AI Implementations
Ethical Considerations
Google Secure AI Framework
Risks With GenAI
Zero Trust Generative AI
Protecting From GenAI aided attacks
Mitigating AI Risks
LAB: Deidentify GenAI Responses

Chapter 3: Attacking AI Vulnerabilities

AI Algorithms, Data Sets, Models
OWASP AI Security Risks
Prompt Engineering
AI vulnerabilities
Attacks Against Classifiers
NIST Adversarial ML Taxonomy
Adversarial ML Threat Matrix
AI Red Teaming
LAB: Penetration Testing an AI System

Chapter 4: Securing AI

Mitigating AI Risks
GenAI Monitoring and Logging
AI Gateways
Agent Gateways
AI Security checklist
LAB: Safeguarding With Gemini AI

Chapter 5: AI-Powered Hacking

Using AI to Hack
GenAISocial Engineering
Deepfakes
AI infused Hacking
Long Con AI
LAB: Enhance Hacking With GenAI

Chapter 6: Defending Security Operations with AI

SecOps
AI-Based Security Processes
IT Operations and Cloud AI
GenAIRed Teaming
AI Security Tools
Google AI SecOps
Cybersecurity Copilot
LAB: Analyze a Codebase With Gemini
LAB: SecOps Threat Hunting With AI
LAB: Anatomy of an AI Model Attack
LAB: Secure Coding With AI

Chapter 7: Regulating AI Governance

Regulatory Compliance for AI
NIST AI Risk Management Framework
OWASP Security & Governance Checklist
Responsible AI
GenAI Governance Framework

Commercial Pricing

£1,780

3-Day Instructor-Led Training
Developed by a Learning Tree Subject Matter Expert
After-Course Instructor Coaching Included
Available for Private Team Training

Would you like to take this course as a team?

Include dates with afternoon start times

Nov 4 - 6 2:00 pm - 9:30 pm GMT

Toronto or Virtual
Nov 18 - 20 9:00 am - 4:30 pm GMT

London or Virtual
Guaranteed-to-Run - You can rest assured this class will not be canceled. Delivery format is subject to change – please call Customer Service if you have any questions.
Dec 9 - 11 2:00 pm - 9:30 pm GMT

Herndon, VA or Virtual
Dec 16 - 18 3:00 pm - 10:30 pm GMT

Austin or Virtual
Jan 20 - 22 2:00 pm - 9:30 pm GMT

Ottawa or Virtual
Feb 3 - 5 2:00 pm - 9:30 pm GMT

New York or Virtual
Feb 17 - 19 9:00 am - 4:30 pm GMT

London or Virtual
Apr 14 - 16 2:00 pm - 9:30 pm BST

Toronto or Virtual
May 19 - 21 9:00 am - 4:30 pm BST

London or Virtual
May 19 - 21 2:00 pm - 9:30 pm BST

Herndon, VA or Virtual
Jun 2 - 4 3:00 pm - 10:30 pm BST

Austin or Virtual
Jun 23 - 25 2:00 pm - 9:30 pm BST

Ottawa or Virtual
Jul 7 - 9 2:00 pm - 9:30 pm BST

New York or Virtual
Aug 25 - 27 2:00 pm - 9:30 pm BST

Toronto or Virtual
Sep 22 - 24 2:00 pm - 9:30 pm BST

Herndon, VA or Virtual

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AI and Cyber Security: Attack and Defend FAQs

Yes. Labs provide practical experience with language models, data de-identification, AI penetration testing, AI-assisted threat hunting, codebase analysis, secure coding, and the investigation of AI model attacks.

The course introduces the NIST AI Risk Management Framework, NIST Adversarial Machine Learning Taxonomy, Google Secure AI Framework, OWASP AI security risks, and OWASP security and governance guidance.

Advanced AI expertise is not required. However, participants will benefit from a foundational understanding of cybersecurity, IT systems, cloud environments, or software development. Some programming familiarity may also be helpful for completing the technical labs.

AI and Cyber Security: Attack and Defend

AI and Cyber Security: Attack and Defend Delivery Methods

AI and Cyber Security: Attack and Defend Course Information

AI and Cyber Security: Attack and Defend Course Outline

Learning Objectives

Live Instructor £1,780

AI and Cyber Security: Attack and Defend FAQs

Does the course include hands-on labs?

What AI security frameworks and standards are covered?

Do I need previous AI or programming experience?

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