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Machine Learning Security Principles

You're reading from   Machine Learning Security Principles Keep data, networks, users, and applications safe from prying eyes

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Product type Paperback
Published in Dec 2022
Publisher Packt
ISBN-13 9781804618851
Length 450 pages
Edition 1st Edition
Languages
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Author (1):
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John Paul Mueller John Paul Mueller
Author Profile Icon John Paul Mueller
John Paul Mueller
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Table of Contents (19) Chapters Close

Preface 1. Part 1 – Securing a Machine Learning System
2. Chapter 1: Defining Machine Learning Security FREE CHAPTER 3. Chapter 2: Mitigating Risk at Training by Validating and Maintaining Datasets 4. Chapter 3: Mitigating Inference Risk by Avoiding Adversarial Machine Learning Attacks 5. Part 2 – Creating a Secure System Using ML
6. Chapter 4: Considering the Threat Environment 7. Chapter 5: Keeping Your Network Clean 8. Chapter 6: Detecting and Analyzing Anomalies 9. Chapter 7: Dealing with Malware 10. Chapter 8: Locating Potential Fraud 11. Chapter 9: Defending against Hackers 12. Part 3 – Protecting against ML-Driven Attacks
13. Chapter 10: Considering the Ramifications of Deepfakes 14. Chapter 11: Leveraging Machine Learning for Hacking 15. Part 4 – Performing ML Tasks in an Ethical Manner
16. Chapter 12: Embracing and Incorporating Ethical Behavior 17. Index 18. Other Books You May Enjoy

Defining hacker goals

Previous chapters have discussed various kinds of hacker goals in specific scenarios. Chapter 4, in particular, pays attention to the hacker as part of the threat environment. So, you already know that hackers have goals such as stealing money or credentials, causing mayhem seemingly for the sheer joy of doing so, and working for others to perform espionage, sabotage, or forms of political maneuvering. These are all effects of the hacker’s personal goals; the outcome after a hacker chooses a target and an attack vector. However, they don’t really look at why the hacker would perform an attack in the first place. Obviously, hackers are relatively smart, so they could earn a legitimate living doing something else, so why be a hacker? The sections that follow look at hacker goals from a more behavioral stance than previous chapters have done and assess the ability of ML to help you ascertain those behavioral goals.

Is the hacker smart, or are people...

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