Course Purpose
Course Purpose
The purpose of this course is to help learners explore the application of artificial intelligence (AI)
in the field of cybersecurity. It covers the basics of cybersecurity, the fundamentals of AI, and the
ways in which AI techniques can be used to detect, prevent, and respond to cyber threats. The course also
addresses the security challenges posed by AI systems themselves and discusses the ethical and legal
considerations related to AI and cybersecurity.
Course Learning Outcomes
Expected Learning Outcomes (ELOs)
- ELO 1: Understand the basic concepts of cybersecurity and artificial intelligence.
- ELO 2: Explore how AI can be applied to enhance cybersecurity measures.
- ELO 3: Analyze the potential risks and vulnerabilities associated with AI systems.
- ELO 4: Develop practical skills in implementing AI-based cybersecurity solutions.
Course Content
Module Overview: Cybersecurity and Artificial Intelligence
- Overview of Cybersecurity: Definition and importance of cybersecurity; types of cyber threats and attacks; key cybersecurity principles.
- Cybersecurity Frameworks and Standards: NIST Cybersecurity Framework; ISO/IEC 27001; other relevant standards and best practices.
- Fundamentals of Artificial Intelligence: Machine Learning, Deep Learning, Neural Networks; AI techniques, algorithms, and tools; introductory programming with Python and R.
- AI for Threat Detection and Prevention: Anomaly detection; intrusion detection systems (IDS); AI-based malware analysis.
- AI for Incident Response and Recovery: Automated incident response; AI in digital forensics; AI-powered threat intelligence.
- AI in Security Operations Centers (SOC): AI-driven security monitoring; case studies of AI in SOC environments.
- Vulnerabilities in AI Systems: Adversarial machine learning; data poisoning; model inversion and extraction attacks.
- Protecting AI Models: Defensive techniques against adversarial attacks; secure AI training and deployment; privacy-preserving machine learning.
- Ethical Implications of AI in Cybersecurity: Bias and fairness; ethical use of AI in surveillance and law enforcement; legal and compliance considerations.
- Real-World Case Studies: Successful AI-driven cybersecurity implementations; lessons learned from AI-related security incidents.
CBET ALIGNMENT
| CBET Elements | Learning Engagement Strategies | Expected Learning Outcomes |
|---|---|---|
| Communication and Collaboration | Group discussions on core cybersecurity and AI concepts; peer review of AI-enhanced security solutions. | ELO1, ELO2, ELO4 |
| Critical Thinking and Problem Solving | Analyze real-world cybersecurity incidents and evaluate how AI could mitigate or prevent them. | ELO2, ELO3, ELO4 |
| Creativity and Imagination | Design innovative AI-driven tools or models to detect and respond to cyber threats. | ELO2, ELO4 |
| Digital Literacy | Conduct hands-on labs using AI and cybersecurity tools (e.g., TensorFlow, Scikit-learn, Snort, Splunk) to identify, classify, and respond to attacks. | ELO1, ELO4 |
| Citizenship | Engage in ethical discussions on responsible AI use in cybersecurity, including privacy and data protection concerns. | ELO1, ELO3 |
| Learning to Learn | Undertake self-directed exploration of current AI frameworks and emerging cybersecurity technologies through research and online labs. | ELO1, ELO2, ELO3 |
| Social Justice | Role-play scenarios exploring how AI misuse in cybersecurity (e.g., surveillance, bias in threat detection) affects different social groups. | ELO3, ELO4 |
| Integrity | Review case studies on AI ethics breaches in cybersecurity (e.g., biased algorithms, data misuse) and propose corrective measures. | ELO3, ELO4 |
| Patriotism | Debate national versus global cybersecurity and AI governance policies, emphasizing Kenya’s and Africa’s strategic interests. | ELO1, ELO3 |
| Life Skills | Simulate real-world cyber defense exercises using AI tools; manage incident response teams to build decision-making and leadership capacity. | ELO2, ELO4 |
| Community Service Learning | Collaborate with local organizations to assess and improve their cybersecurity posture using AI-based tools and awareness programs. | ELO2, ELO4 |
| Pertinent and Contemporary Issues | Participate in expert-led seminars on emerging topics such as AI-driven phishing, adversarial AI, and quantum-safe security. | ELO2, ELO3 |