Code: USD75OFF
This is the code repository for Machine Learning Security Principles, published by Packt.
Use various methods to keep data, networks, users, and applications safe from prying eyes
Machine learning is an important technology for getting more out of data today. Scientists use machine learning to discover new techniques or to create new kinds of data. Businesses use machine learning to detect credit card fraud, monitor networks, implement factory processes, and to achieve all sorts of other goals where humans and AI work side-by-side as explained in Part 1 of this book. Part 2 of this book covers all of the environments in which machine learning is commonly used and illustrates the security threats that plague them using code, graphics, and real world references. Hackers don’t always damage or steal data, or use it to perform social attacks on a business. Sometimes they 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. Examples in Part 3 of this book show how to detect hacker behaviors in the modern computing environment. Obtaining data in an ethical manner is important because the very act behaving ethically reduces the security risk associated with data. The simple act of removing Personally Identifiable Information (PII) from a dataset, as illustrated in Part 4 of this book, reduces the risk of social engineering attacks, while simultaneously keeping users safe.
This book covers the following exciting features:
- Learn methods to detect and prevent illegal access to your system
- Discover detection techniques when access does occur
- Employ machine learning techniques to determine motivations
- Mitigate hacker access once security is breached
- Perform statistical measurement and behavior analysis
- Repair damage to your data and applications
- Use ethical data collection methods to reduce security risks
If you feel this book is for you, get your copy today!
All of the code is organized into folders.
The code will look like the following:
import getpass
user = getpass.getuser()
pwd = getpass.getpass("User Name : %s" % user)
Following is what you need for this book: Whether you’re a data scientist, researcher, or manager interested in machine learning techniques from various perspectives, you need this book because security has become a major headache for all three groups. Most resources are written by PhD candidates in a language that only they understand. This book presents security in a way that's easy to understand and employs a host of diagrams to explain concepts to visual learners. The book assumes that you're familiar with machine learning concepts and it helps if you already know a programming language, with an emphasis on Python knowledge.
With the following software and hardware list you can run all code files present in the book (Chapter 1-12).
| Chapter | Software required | OS required |
|---|---|---|
| 1-12 | Anaconda 3, 2020.07 | Windows 7, 10, or 11, macOS 10.13 or above Linux (Ubuntu, RedHat, and CentOS 7+ all tested) |
| 1-12 | Python 3.8 or higher (version 3.9.x is highly recommended, versions above 3.10.7 aren’t recommended or tested | The test system uses this hardware, which is considered minimal: Intel i7 CPU 8 GB RAM 500 GB hard drive |
| 1-12 | NumPy 1.18.5 or greater (version 1.21.x is highly recommended) | |
| 1-12 | Scikit-learn 0.23.1 or greater (version 1.0.x is highly recommended) | |
| 1-12 | Pandas 1.1.3 or greater (version 1.4.x is highly recommended) |
John Paul Mueller is a seasoned author and technical editor. He has writing in his blood, having produced 121 books and more than 600 articles to date. The topics range from networking to artificial intelligence and from database management to heads-down programming. Some of his current books include discussions of data science, machine learning, and algorithms. He also writes about computer languages such as C++, C#, and Python. His technical editing skills have helped more than 70 authors refine the content of their manuscripts. John has provided technical editing services to a variety of magazines, performed various kinds of consulting, and he writes certification exams.
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