Leverage the power of Artificial Intelligence to automate, scale, and enhance threat modeling, transforming how you identify, assess, and mitigate security risks.
What You Will Learn:
Understand and apply core threat modeling methodologies such as STRIDE and PASTA to evaluate security risks in system architecture.
Explain foundational AI/ML concepts and how they apply to cybersecurity use cases like anomaly detection and behavioral classification.
Execute structured threat modeling workflows, including data flow diagramming, threat identification, and risk mitigation planning.
Compare and integrate traditional and AI-augmented threat modeling approaches, leveraging LLMs for scenario generation and prioritization.
Prepare and process security-relevant data for LLM-powered threat analysis, including threat intelligence feeds, CVEs, logs, and architecture data.
Use model evaluation metrics (precision, recall, F1-score) to assess threat detection performance and drive risk-based decision-making.
Leverage GenAI tools such as ChatGPT and StrideGPT to accelerate threat modeling, documentation, and control mapping.
Identify emerging threats in AI systems and apply best practices for AI-specific threat modeling across the development lifecycle.
Pursue continuing education and certification, including EC-Council C|TIA, OWASP AI Testing Guide, and the NIST AI Risk Management Framework.
