Overview
Discover how to leverage AI and machine learning for cybersecurity challenges, from anomaly detection to combating ransomware, malware, and phishing, including using large language models.
Syllabus
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- Introduction to AI in Cybersecurity
-- Overview of AI and machine learning concepts
-- Importance of AI in the cybersecurity landscape
- Machine Learning Techniques for Cybersecurity
-- Supervised and unsupervised learning methods
-- Feature selection and data preprocessing
-- Model evaluation and performance metrics
- Anomaly Detection
-- Types of anomalies in cybersecurity
-- Techniques for anomaly detection
-- Implementing anomaly detection models
- AI Applications in Ransomware Detection
-- Understanding ransomware behavior
-- Machine learning models for ransomware detection
-- Case studies and real-world applications
- Malware Analysis with AI
-- Static and dynamic analysis of malware
-- Machine learning techniques for malware classification
-- Advanced threat detection using AI
- AI Strategies for Phishing Detection
-- Identifying phishing attacks
-- Leveraging AI to detect phishing attempts
-- Implementations and practical tools
- Leveraging Large Language Models for Cybersecurity
-- Introduction to large language models (LLMs)
-- Using LLMs for threat intelligence and analysis
-- Enhancing incident response with LLMs
- Ethical Considerations and Challenges
-- Addressing biases in AI models
-- Ethical use of AI in cybersecurity
-- GDPR and data privacy concerns
- Hands-on Labs and Projects
-- Practical exercises for anomaly detection
-- Building models for ransomware and malware detection
-- Phishing detection with natural language processing
- Conclusion and Future Trends
-- Emerging AI technologies in cybersecurity
-- Future of AI-driven cybersecurity solutions
-- Continuous learning and upskilling resources
- Assessment and Certification
-- Course project and practical assessment
-- Final exam and course certification criteria
Taught by
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On-Demand
