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Artificial Intelligence for Cybersecurity

via LinkedIn Learning


Learn how to leverage artificial intelligence (AI) to solve complex problems in the field of information security. Along the way, explore the risks of using AI for security.

Artificial intelligence (AI)—when leveraged with preparation and guardrails—is a game-changing approach to solving complex problems in cybersecurity. In this course, instructor Sam Sehgal delves into AI in the context of information security, providing use cases and practical examples that lend each concept a real-world context. Sam goes over the six main disciplines of AI and explains how to apply these disciplines to solve pressing security problems, such as the challenges of data at scale and speed in threat response. He covers machine learning techniques and their suitability for security issues, as well as the general limitations and risks of using AI for security. Plus, he shares how to best prepare your organization to apply AI-driven security.


  • Applying AI to information security
1. Demystifying Artificial Intelligence for Security
  • What is artificial intelligence?
  • Artificial intelligence for security
  • Foundational disciplines of AI
  • Discipline of learning
2. Security Objectives and Approaches
  • End-to-end security framework
  • Security controls
3. Leveraging AI to Solve Complex Security Problems
  • Problem of scale
  • Problem of context
  • Problem of precision and accuracy
  • Problem of speed
4. Machine Learning for Security
  • Categories of machine learning
  • Prediction by regression
  • Classification of good versus bad
  • Clustering, pattern, and anomaly detection
  • Synthetic data generation
5. Practical Considerations, Risks, and Limitations
  • Three ways AI can fail you
  • One: Limitations and poor implementation
  • Two: Attack against your AI implementation
  • Three: Use of AI by criminals
  • Getting your organization ready for AI
  • Evaluating AI-based products
  • Next steps

Taught by

Sam Sehgal

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