AI in Cybersecurity

TEACHING UNIT 1. FUNDAMENTALS OF AI APPLIED TO CYBERSECURITY Overview of key AI architectures in the context of digital security Challenges and opportunities of AI in protecting systems and data Data sources and preprocessing for cybersecurity models Google Cloud AI as a platform and tool for AI development in cybersecurity TEACHING UNIT 2. INTELLIGENT THREAT AND ANOMALY DETECTION Machine learning models for malware and virus detection Network and User Behavior Analysis (UEBA) with AI Anomaly-based intrusion detection using neural networks Identification of zero-day attacks and advanced persistent threats (APTs) Unsupervised learning techniques for discovering unknown threats LEARNING UNIT 3. AI FOR VULNERABILITY AND PATCH MANAGEMENT Prioritizing vulnerabilities using predictive models Automating the identification and classification of security flaws Predicting exploits and attack surfaces with AI Optimizing risk-based patching strategies AI-assisted static and dynamic code analysis LEARNING UNIT 4. PUBLIC SAFETY AND EMERGENCY RESPONSE WITH AI Generating adversarial attacks for stress testing Automating penetration testing and vulnerability scanning Developing intelligent honeypots to deceive attackers Automated incident response and threat containment Reinforcement learning models for cyberdefense strategies TEACHING UNIT 5. PRIVACY AND DATA PROTECTION WITH AI Anonymization and de-identification of sensitive data using AI AI-assisted data leak detection and prevention (DLP) Security in the processing of personal data using AI techniques Differential privacy and homomorphic encryption applied with AI Intelligent identity and access management (IAM) TEACHING UNIT 6. AI IN CLOUD AND INFRASTRUCTURE CYBERSECURITY Threat monitoring and detection in cloud environments Container and microservices security using AI Protection of critical infrastructure and industrial control systems (ICS/SCADA) Risk analysis and compliance in multicloud environments Implementation of AI for software supply chain security TEACHING UNIT 7. CYBER RESILIENCE AND AI-ASSISTED RECOVERY Assessing system resilience against cyberattacks Planning and simulating crisis scenarios with AI Automated disaster recovery and system restoration Digital Forensics and Persistence Detection with AI Optimization of Post-Attack Business Continuity Plans LEARNING UNIT 8. THE FUTURE OF AI IN CYBERSECURITY Explainable AI (XAI) in Security Decision-Making Adversarial attacks against AI models and countermeasures The role of quantum computing in cybersecurity Emerging trends at the intersection of AI and cybersecurity Human-AI collaboration in cybersecurity teams (Google Security Operations)