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CyberSecurity and AI Education
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Machine Learning for Cybersecurity
M0: *Getting Started with Docker on ML for CyberSecurity
Overview
Helloworld example
M1: Naive Bayes for spam email filtering
Pre-Lab
Hands-on Lab Practice
Post-Add-on-Lab
M2: *Logistic Regression for financial fraud prediction
Pre-Lab
Hands-on Lab Practice
Post-Add-on-Lab
M3: Support Vector Machines for malware analysis
Pre-Lab
Hands-on Lab Practice
Post-Add-on-Lab
M4: Neural network algorithms for network DOS detection
Pre-Lab
Hands-on Lab Practice
Post-Add-on-Lab
M5: Decision Tree for website phishing
Pre-Lab
Hands-on Lab Practice
Post-Add-on-Lab
M6: Deep learning for malware classification and protection
Pre-Lab
Hands-on Lab Practice
Post-Add-on-Lab
M7: Deep Learning Based Medical Treatments for Novel Coronavirus
Pre-Lab
Hands-on Lab Practice
Post-Add-on-Lab
M8: K-Means clustering for network traffic monitoring
Pre-Lab
Hands-on Lab Practice
Post-Add-on-Lab
M9: Decision Tree for malicious web application detections
Pre-Lab
Hands-on Lab Practice
Post-Add-on-Lab
M10: KNN Classification for user behavior anomaly detection
Pre-Lab
Hands-on Lab Practice
Post-Add-on-Lab
Cybersecurity for Machine learning
M1: Adversarial input
Pre-Lab
Hands-on Lab Practice
Post-Add-on-Lab
M2: Data poisoning
Pre-Lab
Hands-on Lab Practice
Post-Add-on-Lab
M3: Model stealing
Pre-Lab
Hands-on Lab Practice
Post-Add-on-Lab
M4: Mitigating attack threats to ML software with Denial-Of-Service
Pre-Lab
Hands-on Lab Practice
Post-Add-on-Lab
M5: Mitigating attack threats to ML software with Arbitrary Code Execution
Pre-Lab
Hands-on Lab Practice
Post-Add-on-Lab
M6: Feedback Weaponization Attack
Pre-Lab
Hands-on Lab Practice
Post-Add-on-Lab
M7: Privacy attack
Pre-Lab
Hands-on Lab Practice
Post-Add-on-Lab
M8: Backdoor attack
Pre-Lab
Hands-on Lab Practice
Post-Add-on-Lab
CyberSecurity and AI Education
M1. Naive Bayes for spam email filtering
Pre-Lab
Hands-on Lab Practice
Post-Add-on-Lab
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