Book Image

Machine Learning Security Principles

By : John Paul Mueller
Book Image

Machine Learning Security Principles

By: John Paul Mueller

Overview of this book

Businesses are leveraging the power of AI to make undertakings that used to be complicated and pricy much easier, faster, and cheaper. The first part of this book will explore these processes in more depth, which will help you in understanding the role security plays in machine learning. As you progress to the second part, you’ll learn more about the environments where ML is commonly used and dive into the security threats that plague them using code, graphics, and real-world references. The next part of the book will guide you through the process of detecting hacker behaviors in the modern computing environment, where fraud takes many forms in ML, from gaining sales through fake reviews to destroying an adversary’s reputation. Once you’ve understood hacker goals and detection techniques, you’ll learn about the ramifications of deep fakes, followed by mitigation strategies. This book also takes you through best practices for embracing ethical data sourcing, which reduces the security risk associated with data. You’ll see how the simple act of removing personally identifiable information (PII) from a dataset lowers the risk of social engineering attacks. By the end of this machine learning book, you'll have an increased awareness of the various attacks and the techniques to secure your ML systems effectively.
Table of Contents (19 chapters)
Part 1 – Securing a Machine Learning System
Part 2 – Creating a Secure System Using ML
Part 3 – Protecting against ML-Driven Attacks
Part 4 – Performing ML Tasks in an Ethical Manner

Defending against Hackers

Previous chapters have addressed a wide variety of threats and an even wider variety of threat sources. Most people would be having full-on bouts of paranoia about now! The fact is that these threats and threat sources are real, but most of them become a threat source as a secondary matter. For example, an employee doesn’t normally join your organization with the thought of stealing as much as possible from you and then running away. The very few employees that actually do steal something and then run away do it later after they have been in your business for a while. Hackers, on the other hand, start out with the idea of stealing, damaging, or monitoring something in your business. They’ve never had any other idea in mind. The orientation and priority of the attack are why defending against hackers is different from defending against other threats and why the separate treatment in this chapter is important.

Of course, hackers are not superhuman...