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)
1
Part 1 – Securing a Machine Learning System
5
Part 2 – Creating a Secure System Using ML
12
Part 3 – Protecting against ML-Driven Attacks
15
Part 4 – Performing ML Tasks in an Ethical Manner

Preface

Machine learning is the most important new technology today for getting more out of data. It can reveal patterns that aren’t obvious, for example, but it requires data – lots of it. Data gathering isn’t just about data. It affects users and requires the use of applications to clean, manipulate, and analyze the data. Scientists use machine learning to discover new techniques or to create new kinds of data, such as the generation of various kinds of art based on existing inputs or the advancement of medicine through better imaging. Businesses use machine learning to perform tasks, such as detecting credit card fraud, monitoring networks, and implementing factory processes, and to achieve all sorts of other goals where humans and AI work side-by-side.

Hackers don’t always damage data; sometimes they steal it or use it to perform social attacks on a business. Sometimes they simply want money or other goods, and machine learning offers an avenue for acquiring them. A hacker may not steal anything at all – perhaps the target is someone’s reputation. It may surprise you to learn that hackers often use machine learning applications themselves to perform a kind of dance with your machine learning-based security to overcome it. However, hackers have behavioral patterns, and knowing how to detect those patterns is important in the modern computing environment.

Obtaining data in an ethical manner is important because the very act of behaving ethically reduces the security risk associated with data. However, hackers don’t necessarily target users and their data. Perhaps they’re interested in your organization’s trade secrets or committing fraud. They might simply be interested in lurking in the background and committing mischief. So, just keeping your data secure as a means of protecting your machine learning investment isn’t enough. You need to do more.

This book helps you get the big picture from a machine learning perspective using all the latest research available on methods that hackers use to break into your system. It’s about the whole system, not just your application. You will discover techniques that help you gather data ethically and keep it safe, while also preventing all sorts of illegal access methods from even occurring. In fact, you will use machine learning as a tool to keep hackers at bay and discover their true intent for your organization.