Hands-On Machine Learning for Cybersecurity: Safeguard your system by making your machines intelligent using the Python ecosystem (PDF)

Description

Key Features

• Learn machine learning algorithms and cybersecurity fundamentals
• Automate your daily workflow by applying use cases to different aspects of security
• Implement smart machine learning solutions to detect various cybersecurity problems

Book Description

Organizations are increasingly vulnerable to many cybersecurity threats which can lead to significant financial losses, making smart data security more important than ever. In this book, you’ll use different tools and techniques to solve a variety of significant problems that exist in the cybersecurity domain.

The book begins by introducing you to the basics of machine learning in cybersecurity using Python and its libraries. You will then explore various machine learning domains, such as time series analysis and ensemble modeling. As you progress, you will implement various examples such as building a system to identify malicious URLs, and creating a program to detect fraudulent emails and spam. Later, you will learn how to make effective use of the k-means algorithm to develop a solution for detecting and alerting you about any malicious activity in the network. In addition to this, you’ll get up to speed with implementing biometric authentication and fingerprint scanning to validate whether someone is a legitimate user or not. Finally, you will see how you can use TensorFlow for cybersecurity, along with understanding how deep learning is effective for creating models and training systems.

By the end of this book, you will have learned how to effectively use the Python ecosystem and machine learning algorithms for cybersecurity.