Learning Security Frameworks

Learning Security Frameworks
Learning Security Frameworks
English | MP4 | AVC 1280×720 | AAC 48KHz 2ch | 0h 47m | 329 MB

Security frameworks are designed to help organizations boost their security posture. Such frameworks provide security practitioners—and their business partners—with a common set of practices to follow, as well as a baseline that makes it easier to report on improvements. In this course, join Mandy Huth as she covers the top four frameworks available, goes over how the frameworks compare, and shares how you can actually map your security controls across multiple frameworks. Mandy also shows how to determine your core security set, stepping through how to define what you’ll do and how you’ll measure it, and then prove that you did what you sought out to do. Throughout the course, she shares best practices that can help you start leveraging a security framework in your own company.

Topics include:

  • Picking the right security framework
  • Why are security frameworks important?
  • Global, federal, and state cybersecurity regulations
  • PCI and credit card payments
  • CIS critical security controls
  • Comparing the top four security frameworks
  • Mapping process and technical controls
  • Augmenting frameworks with GRCs
  • Developing a security mindset
Table of Contents

1 Build complete solutions with machine learning services
2 What you should know
3 About using cloud services
4 Business scenarios for machine learning
5 Which algorithm should you use
6 GCP AI servers vs. platforms
7 Enable GCP ML APIs
8 Data preparation with Cloud Dataflow and Cloud Dataprep
9 An ML notebook in action Colaboratory
10 An ML notebook in action Set up Cloud Datalab
11 An ML notebook in action Use Cloud Datalab
12 Overview of GCP ML APIs
13 Predict via the Cloud Vision API for images
14 Predict via the Cloud Video Intelligence API for video
15 Predict via the Natural Language API for NLP
16 Predict via the Text-to-Speech API
17 Predict via the Speech-to-Text API
18 Predict via the Cloud Translation API
19 Predict via BigQuery ML
20 Understand Cloud AutoML services
21 Understand AutoML Vision
22 Prepare data and labels for AutoML Vision
23 Train model for AutoML Vision
24 Evaluate model with AutoML Vision
25 Predict using a trained AutoML Vision model
26 Why build custom ML models
27 Using containers to host ML models
28 Use Cloud ML Engine
29 Evaluate Cloud ML Engine output
30 Scale custom ML models
31 Understanding deep learning
32 Work with TensorBoard
33 Work with Keras for TensorFlow
34 GPUs and TPUs for TensorFlow
35 TensorFlow for JavaScript and mobile
36 Chatbot with ML
37 Image search with Cloud Vision and Cloud ML
38 GCP serverless machine learning architecture
39 GCP machine learning with structured data
40 GCP ML service for IoT apps
41 Next steps
1 Picking the right security framework
2 Who uses security frameworks
3 Why are security frameworks important
4 Definitions
5 Overview of the major frameworks
6 Other frameworks to consider
7 Cybersecurity regulations
8 Risk assessment and the SIG
9 PCI and credit card payments
10 CIS critical security controls
11 NIST 800-53 Guidance for US companies
12 ISO 27001 A global approach with certification
13 How the frameworks compare
14 Mapping process controls
15 Mapping technical controls
16 Deciding on a framework
17 The control families
18 The measures
19 The assurances
20 Augmenting frameworks with GRCs
21 Developing a security mindset
22 Next steps