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Zero Trust Overview and Playbook Introduction

Zero Trust Overview and Playbook Introduction

By : Mark Simos, Nikhil Kumar
4.8 (13)
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Zero Trust Overview and Playbook Introduction

Zero Trust Overview and Playbook Introduction

4.8 (13)
By: Mark Simos, Nikhil Kumar

Overview of this book

Zero Trust is cybersecurity for the digital era and cloud computing, protecting business assets anywhere on any network. By going beyond traditional network perimeter approaches to security, Zero Trust helps you keep up with ever-evolving threats. The playbook series provides simple, clear, and actionable guidance that fully answers your questions on Zero Trust using current threats, real-world implementation experiences, and open global standards. The Zero Trust playbook series guides you with specific role-by-role actionable information for planning, executing, and operating Zero Trust from the boardroom to technical reality. This first book in the series helps you understand what Zero Trust is, why it’s important for you, and what success looks like. You’ll learn about the driving forces behind Zero Trust – security threats, digital and cloud transformations, business disruptions, business resilience, agility, and adaptability. The six-stage playbook process and real-world examples will guide you through cultural, technical, and other critical elements for success. By the end of this book, you’ll have understood how to start and run your Zero Trust journey with clarity and confidence using this one-of-a-kind series that answers the why, what, and how of Zero Trust!
Table of Contents (13 chapters)
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2
Chapter 2: Reading the Zero Trust Playbook Series

What are the limitations of AI?

AI technology will be powerful and transformative, but AI is not a magic silver bullet solution for security or any other problems. AI has very real and significant limitations, and it is far from the fully independent human-like artificial general intelligence (AGI) we frequently see portrayed in movies and TV shows.

The main limitation is that AI models don’t truly understand content in the complex and rich ways that humans do. AI will also naturally reflect and propagate any biases in its data, whether or not these biases are known and documented.

Let’s take a quick look at these key limitations of AI.

AI models do not “understand” anything

While generative AI appears to “understand” things on the surface, it is only imitating the original content it was trained on. This extremely shallow “understanding” is similar to fake buildings (façades) on a Western movie set – these...

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