Leverage AI in cybersecurity while ensuring secure, compliant, and governed deployment
This course explores the use of artificial intelligence in organizational operational security. It covers the opportunities offered by AI for threat detection and incident response automation, as well as the risks and ethical issues associated with its use.
Is it for you ?
This course is intended for security managers (CISO, CIO), operational and IT managers, digital project managers, cybersecurity consultants, and anyone involved in secure digital transformation projects.
Prerequisites
Basic knowledge of IT security or risk management. General digital literacy.
What You'll Walk Away With
- ✓ Understand AI fundamentals and their practical applications in operational security
- ✓ Use AI to detect anomalies, automate incident response, and enhance monitoring
- ✓ Identify AI-specific risks, including model vulnerabilities and adversarial attacks
- ✓ Implement AI governance aligned with security policies and regulatory requirements
- ✓ Develop a secure AI integration plan with cross-functional collaboration
Training content
1 Day 1: Fundamentals of AI and operational security
2 Chapter 1: Introduction to AI
- Definitions, key concepts (machine learning, deep learning)
- Areas of application in the enterprise
- AI and process automation
3 Chapter 2: Overview of AI uses in security
- Intrusion detection and behavioral analysis
- Incident response automation
- Predictive monitoring and preventive maintenance
Workshop 1: Demonstration of an AI cybersecurity tool
- Log analysis with AI
- Real-time anomaly detection
4 Chapter 3: New risks induced by AI
- AI model vulnerabilities
- Adversarial attacks
- False confidence in automated systems
5 Day 2: Governance, ethics, and secure integration of AI
6 Chapter 4: AI governance in an operational context
- Roles and responsibilities
- Integration into security policies
- Auditability and traceability of AI decisions
7 Chapter 5: Ethical and regulatory issues
- Algorithmic bias and discrimination
- Compliance with GDPR and the upcoming AI Act
- Transparency and explainability of AI decisions
Workshop 2: Case study – Security incident related to AI
- Analysis of a real or fictional case
- Identification of vulnerabilities and recommendations
8 Chapter 6: Best practices for secure AI
- Secure lifecycle of AI models
- Collaboration between security and data science teams
- Implementation of an AI & security charter
Workshop 3: Development of an AI + security integration plan
- Group work
- Presentation and peer feedback
📌 Practical information
Our training sessions are offered in Montreal or Quebec City, in person or in a virtual classroom. Dates and locations are specified when you select your session below. If you have any questions, check out our FAQ.
