Unit 1 Artificial Intelligence Core Concepts and Tools

8 lecture hours

• Evolution of AI: from expert systems to data mining
• Types of machine learning
• Algorithm training and optimization
• AI in the context of cyber security
• Setting up AI for cyber security arsenal
• Python for AI and cyber security

Unit 2 Detecting Cyber Security Threats using AI

10 lecture hours

• Detecting spam with perceptron
• Spam detection with SVMs
• Phishing detection with logistic regression and decision trees
• Spam detection with Naïve Bayes
• Malware analysis at glance
• Decision tree malware detectors
• detecting metamorphic malware with HMMs
• Advanced malware detection with deep learning
• Network Anomaly detection techniques
• Network attack classification
• Detecting botnet topology
• Different ML algorithms for botnet detection

Unit 3 Protecting Sensitive Information and Assets

8 lecture hours

• Authentication abuse prevention
• account reputation scoring
• User authentication with keystroke recognition
• Biometric authentication with facial recognition
• introducing fraud detection algorithm
• Predictive analytics for credit card fraud detection
• Evaluating the quality of predictions

Unit 4 Evaluating and Testing AI Arsenal

8 lecture hours

• Best practices for featuring engineering
• evaluating a detector’s performance with ROC, using cross-validation for algorithms
• Evading ML detectors
• Challenging ML anomaly detection
• Testing for data and model quality
• Ensuring securing and reliability

Unit 5 Future Aspects

• Latest Developments in Artificial Intelligence for enhancement of Cyber Security for organizations. 6 10