English | MP4 | AVC 1280×720 | AAC 48KHz 2ch | 1h 15m | 177 MB
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.
Topics include:
- Foundational disciplines of artificial intelligence
- Identifying security activities at different stages
- How AI can help you tackle problems of scale
- Using AI to avoid false positives
- How AI can address issues before they become threats
- Using clustering methods with security problems
- Preparing your organization for AI
- Evaluating AI tools in the market
Table of Contents
1 Applying AI to information security
2 What is artificial intelligence
3 Artificial intelligence for security
4 Foundational disciplines of AI
5 Discipline of learning
6 End-to-end security framework
7 Security controls
8 Problem of scale
9 Problem of context
10 Problem of precision and accuracy
11 Problem of speed
12 Categories of machine learning
13 Prediction by regression
14 Classification of good versus bad
15 Clustering, pattern, and anomaly detection
16 Synthetic data generation
17 Three ways AI can fail you
18 One Limitations and poor implementation
19 Two Attack against your AI implementation
20 Three Use of AI by criminals
21 Getting your organization ready for AI
22 Evaluating AI-based products
23 Next steps
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