AI+ Security: Level 3

– Foundations of AI and Machine Learning for Security Engineering
• Core AI and ML Concepts for Security
• AI Use Cases in Cybersecurity
• Engineering AI Pipelines for Security
• Challenges in Applying AI to Security

– Machine Learning for Threat Detection and Response
• Engineering Feature Extraction for Cybersecurity Datasets
• Supervised Learning for Threat Classification
• Unsupervised Learning for Anomaly Detection
• Engineering Real-Time Threat Detection Systems

– Deep Learning for Security Applications
• Convolutional Neural Networks (CNNs) for Threat Detection
• Recurrent Neural Networks (RNNs) and LSTMs for Security
• Autoencoders for Anomaly Detection
• Adversarial Deep Learning in Security

– Adversarial AI in Security
• Introduction to Adversarial AI Attacks
• Defense Mechanisms Against Adversarial Attacks
• Adversarial Testing and Red Teaming for AI Systems
• Engineering Robust AI Systems Against Adversarial AI

– AI in Network Security
• AI-Powered Intrusion Detection Systems
• AI for Distributed Denial of Service (DDoS) Detection
• AI-Based Network Anomaly Detection
• Engineering Secure Network Architectures with AI

– AI in Endpoint Security
• AI for Malware Detection and Classification
• AI for Endpoint Detection and Response (EDR)
• AI-Driven Threat Hunting
• Implementing Lightweight AI Models for Resource-Constrained Devices

– Secure AI System Engineering
• Designing Secure AI Architectures
• Cryptography in AI for Security
• Ensuring Model Explainability and Transparency in Security
• Performance Optimization of AI Security Systems

– AI for Cloud and Container Security
• AI for Securing Cloud Environments
• AI-Driven Container Security
• AI for Securing Serverless Architectures
• AI and DevSecOps

– AI and Blockchain for Security
• Fundamentals of Blockchain and AI Integration
• AI for Fraud Detection in Blockchain
• Smart Contracts and AI Security
• AI-Enhanced Consensus Algorithms

– AI in Identity and Access Management (IAM)
• AI for User Behavior Analytics in IAM
• AI for Multi-Factor Authentication (MFA)
• AI for Zero-Trust Architecture
• AI for Role-Based Access Control (RBAC)

– AI for Physical and IoT Security
• AI for Securing Smart Cities
• AI for Industrial IoT Security
• AI for Autonomous Vehicle Security
• AI for Securing Smart Homes and Consumer IoT

– Capstone Project – Engineering AI Security Systems
• Defining the Capstone Project Problem
• Engineering the AI Solution
• Deploying and Monitoring the AI System
• Final Capstone Presentation and Evaluation