Choose one of the topics by discussing with the instructor, identify dataset availability, identify at least 3
machine algorithms you plan to apply on datasets, identify performance metrics.
The report should include a prelab section highlighting the cybersecurity problem (E.g., CAPTCHA bypassing),
and planned machine learning approaches (e.g., decision tree, KNN), then hands-on lab section that will show
step-by-step using jupyter notebook platform to train and test datasets, and outcome of the training.
M4. SVM for Unauthorized access with CAPTCHA bypass
M5. Decision Tree for Malicious SQL injection prevention
M6. Deep learning for malware classification and protection
M7. Deep learning for anomaly-based intrusion detection
M8. K-Means clustering for network traffic monitoring
M9. Decision Tree for malicious web application detection
M10. KNN Classification for user behavior anomaly detection
Sample Solution