Mastering AI Security Boot Camp
Enhance your expertise with the Mastering AI Security Boot Camp, designed for cybersecurity and AI professionals to protect machine learning models against ever-evolving threats and ensure ethical AI implementation.
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Essential Skills Gained
Analyze AI-driven cyber threats.
Secure machine learning models.
Implement AI-specific defense strategies.
Conduct AI forensic investigations.
Format
- Instructor-led
- 3 days with lectures and hands-on labs.
Audience
- Cybersecurity professionals
- AI engineers
- System administrators
- Data scientists
Description
Artificial intelligence is transforming cybersecurity, both as a tool for protection and as a target for emerging threats. Mastering AI Security Boot Camp provides the hands-on skills needed to analyze AI-driven threats, secure machine learning models, and implement defense strategies that safeguard organizations from evolving attacks. This expert-led, interactive course is designed for cybersecurity professionals, data scientists, system administrators, AI engineers, and IT leaders who need to understand and mitigate the unique security risks associated with AI technologies. Technical managers, project leads, and compliance professionals overseeing AI security initiatives will also gain critical insights into risk management, ethical AI security practices, and incident response strategies. Over three days, you will identify vulnerabilities in AI systems, apply intrusion detection techniques, and strengthen machine learning models against adversarial threats. You will develop practical skills to analyze security incidents, conduct forensic investigations on AI systems, and build response plans that minimize the impact of cyber threats. The course also explores differential privacy, ethical considerations, and the role of AI in cybersecurity automation, ensuring you can balance protection with responsible AI use. With a 50 percent hands-on approach, this course provides real-world exercises where you will simulate AI security attacks, implement defense strategies, and assess AI-driven security risks in practical scenarios. Whether you are actively securing AI systems or guiding AI adoption within your organization, you will leave with the knowledge and skills to protect machine learning applications, strengthen cybersecurity postures, and respond effectively to AI-related security challenges.
Course Outline
Download PDFIntroduction to AI in Security
The Need for AI Security
Exploring AI Threat Landscape
Identify Threats and Implement Protections in AI Systems
Implement AI Security Best Practices
Top Ten Pitfalls to Avoid
Activity: Implementing Basic Security Measures
Benefits of Applying AI to Cybersecurity
Playing Detective: Identifying AI Threats and Vulnerabilities
Inherent threats and vulnerabilities of AI systems
Different types of AI threats
Common AI vulnerabilities
Case studies of major AI-based security breaches
Building the AI Fortress: Defense Mechanisms 101
Safeguard AI systems from security threats
Deep Dive AI Security Measures
AI Defense Mechanisms
AI in intrusion detection and prevention systems
AI in risk assessment and vulnerability management
Activity: Design a basic AI-driven Intrusion Detection System
AI Adversarial Attacks and Defenses
Adversarial attacks Deep Dive
Techniques to defend against adversarial attacks
Implementing defense measures against sample adversarial attacks
Activity: Defending Against Adversarial Attacks
CSI Cyber: A Foray into AI Forensics
How forensic techniques are applied in AI security
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
Activity: Conduct a simple forensic analysis on an AI system
Crisis Averted: Crafting Your AI Incident Response Plan
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
AI Privacy and Ethical Considerations
Navigate privacy and ethics in AI to promote responsible technology use
Privacy risks in AI/ML applications
Understanding differential privacy
Ethical considerations in AI Security
Hands-on Lab: Implementing differential privacy in a machine learning model
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
Bonus Chapters / Addendum
Next steps in Your AI Security Journey
Ethical AI Deeper Dive - Implementing Ethical AI in Everyday Business Practices
Everyday AI Security: Staying Safe and Smart with AI Tools
Course Site References & Additional Information
Glossary of Main Terms, Skills and Key Topics
Next Steps, Follow on Courses & SkillJourneys
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Aaron Steele
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Javier Martin
Justin Gilley
Kathy Le
Kelson Smith
Oussama Azzam
Pascal Rodmacq
Randall Granier
Aaron Steele
Casey Pense
Chris Tsantiris
Javier Martin
Justin Gilley
Kathy Le
Kelson Smith
Oussama Azzam
Pascal Rodmacq
Randall Granier