Search icon CANCEL
Arrow left icon
Explore Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Conferences
Free Learning
Arrow right icon
Arrow up icon
GO TO TOP
Machine Learning Security Principles

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

Arrow left icon
Product type Paperback
Published in Dec 2022
Publisher Packt
ISBN-13 9781804618851
Length 450 pages
Edition 1st Edition
Languages
Arrow right icon
Author (1):
Arrow left icon
John Paul Mueller John Paul Mueller
Author Profile Icon John Paul Mueller
John Paul Mueller
Arrow right icon
View More author details
Toc

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 current network threats

Network threats go well beyond the application level, and it’s unlikely that a single individual would provide support for every protective means that a network will require. For example, developers aren’t going to handle physical security – a security company will likely handle it. However, your ML application may interact with the physical security system by monitoring cameras and other sensors. If you think this is a little futuristic, companies such as Bosch (https://www.boschsecurity.com/xc/en/solutions/video-systems/video-analytics/) and Nelly’s Security (https://www.nellyssecurity.com/blog/articles/what-is-deep-learning-ai-and-why-is-it-important-for-video-surveillance) have products available today. An ML application can look for trends, such as an attacker who is casing a business before attempting to break in. The human monitoring the cameras may not see that the same person shows up on various nights, yet never...

lock icon The rest of the chapter is locked
Register for a free Packt account to unlock a world of extra content!
A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.
Unlock this book and the full library FREE for 7 days
Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of
Renews at €18.99/month. Cancel anytime