AI/ML for Cybersecurity
Scope
Utilizing machine learning and AI to bolster cybersecurity in modern networks.
Key topics
- ML-based threat detection: anomaly recognition, clustering, behavior analysis.
- Common network-layer attacks (ARP spoofing, DHCP spoofing, CAM overflow) and AI-driven mitigation.
- Techniques for malware prediction and automated threat intelligence extraction.
Course features
- Hands-on labs in AI/ML Security Lab.
- Data modeling, model training, and AI policy implementation.
- Coursework includes developing and evaluating ML-based security tools.
