Course in Artificial Intelligence Applied to Cybersecurity la salle campus barcelona

Course in Artificial Intelligence Applied to Cybersecurity Management

Optimize your organization's cybersecurity strategies through the application of Artificial Intelligence.

Nid: 27482
Syllabus
Academic Plan

1. Introduction to Artificial Intelligence and Cybersecurity

  • AI basics
    • Definitions and types of AI
    • AI Applications in Different Industries
  • Cybersecurity fundamentals
    • Basic principles and common threats
    • Importance of cybersecurity in business management
  • Intersection of AI and cybersecurity
    • How AI Can Improve Cybersecurity
    • Use cases and strategic benefits

2. AI techniques in Cybersecurity

  • Machine Learning
    • Basic concepts and applications in cybersecurity
    • Threat detection use examples
  • Deep learning
    • Introduction to Neural Networks
    • Practical applications in cybersecurity
  • Data analysis
    • Using Big Data to identify patterns and anomalies
    • Analysis tools and techniques

3. Practical applications of AI in Cybersecurity

  • Intrusion detection
    • AI-based intrusion detection systems (IDS)
    • Benefits and challenges from a management perspective
  • Malware analysis
    • Using AI to identify and neutralize malware
    • Impact on organizational security
  • Authentication and access control
    • Advanced authentication methods using AI
    • Implementation and management strategies

4. Future trends of practical applications of AI in Cybersecurity

  • Application of AI in networks and cloud environments
    • Using AI to improve network and cloud planning, management, and operation
    • Applying AI in modern, software-based and highly programmable networks
  • Privacy in AI
    • Federated learning and other architectures for distributed learning
    • Privacy attacks against AI models and possible solutions to prevent information leaks

5. Practical workshop I

  • Developing an incident response plan using AI tools
  • Risk assessment and decision-making using AI tools

6. Ethical and compliance considerations

  • Bias and discrimination in AI: how to identify and mitigate them
  • Professional responsability: ethics and best practices
  • Transparency and informed consent: clear communication with customers

7. New regulations on Artificial Intelligence

  • Analysis of the EU Artificial Intelligence Act and other jurisdictions
  • Legal obligations and regulatory compliance

8. Practical workshop II

  • Presentation and feedback: discussion of the projects and key learnings