Cybersecurity in Artificial Intelligence Applications
As artificial intelligence (AI) becomes increasingly embedded in critical systems—from healthcare and finance to transportation and national security—the need to secure AI applications against cyber threats has never been more urgent.
- 5training days
- 5modules
- 10sessions
- 30topics
About the programme
Course Overview
As artificial intelligence (AI) becomes increasingly embedded in critical systems—from healthcare and finance to transportation and national security—the need to secure AI applications against cyber threats has never been more urgent.
AI systems process vast amounts of sensitive data, make autonomous decisions, and interact with other digital platforms, making them attractive targets for adversaries.
Cybersecurity in AI is not just about protecting algorithms; it involves securing training data, defending models against adversarial attacks, ensuring privacy, and maintaining trust in automated outputs.
Threats such as data poisoning, model inversion, and algorithmic manipulation pose serious risks to the integrity and reliability of AI systems.
This 5-day workshop is designed to equip professionals with the knowledge and tools to build secure, resilient AI applications.
Through hands-on sessions, real-world case studies, and practical frameworks, participants will learn how to identify vulnerabilities, implement safeguards, and align AI development with global security standards.
Whether you're developing AI models or deploying them in enterprise environments, this training will help you do so safely and responsibly.
Expected Learning Outcomes
Understand cybersecurity risks specific to AI applications
Identify vulnerabilities in machine learning models and datasets
Apply security controls to protect AI systems from manipulation
Design models resistant to adversarial attacks
Ensure privacy and data protection in AI workflows
Integrate cybersecurity into the AI development lifecycle
Respond to security incidents involving AI systems
Build a roadmap for secure and trustworthy AI deployment
Who Should Attend
AI and machine learning developers
Cybersecurity engineers and analysts
Data scientists and AI researchers
IT and digital transformation leaders
Governance and compliance professionals
Ethical hacking and penetration testing digital collaboration tools
Security consultants in AI environments
Anyone involved in building or securing AI-powered systems
Course Modules
Open any module to see its sessions and topics.
01Foundations of AI and Cybersecurity
Session 1The Intersection of AI and Cybersecurity
- How AI impacts security
- New threat vectors introduced by AI
- Why securing AI matters
Session 2Cyber Threats in AI Systems
- Data poisoning and model manipulation
- Privacy inference and leakage
- Attacks on deep learning environments
02Securing Data and AI Models
Session 1Protecting Training and Testing Data
- Validating data sources
- Data anonymization and encryption
- Access control and data governance
Session 2Defending Machine Learning Models
- Adversarial attack mitigation
- Model hardening techniques
- Security testing for AI models
03Privacy and Compliance in AI
Session 1Privacy-Preserving AI Techniques
- Federated learning and differential privacy
- Managing sensitive data in AI workflows
- Balancing utility and confidentiality
Session 2Regulatory Compliance and Standards
- GDPR, ISO/IEC 23894, and emerging AI regulations
- Policy development for AI security
- Documentation and audit readiness
04Testing and Ethical Hacking of AI Systems
Session 1Security Testing Methodologies for AI
- Behavioral analysis of models
- Vulnerability scanning in AI pipelines
- Evaluating model outputs for anomalies
Session 2Ethical Hacking of AI Applications
- Simulating attacks on AI systems
- Analyzing system responses
- Reporting and remediation strategies
05Integration and Long-Term Security Strategy
Session 1Embedding Security into AI Development Lifecycle
- Secure design, training, and deployment phases
- Collaboration between AI and security digital collaboration tools
- Continuous monitoring and updates
Session 2Building Sustainable AI Security Readiness
- Ongoing training and awareness
- Post-deployment threat detection
- Adapting to future AI-related threats
Complete your registration
We will contact you within one business day to confirm.