Unlock the secrets of malware data science with cutting-edge techniques, AI-driven analysis, and international compliance standards to stay ahead of the ever-evolving cyber threat landscape

Key Features

Get introduced to three primary AI tactics used in malware and detection

Leverage data science tools to combat critical cyber threats

Understand regulatory requirements for using AI in cyber threat management

Purchase of the print or Kindle book includes a free PDF eBook

Book Description

In today''s world full of online threats, the complexity of harmful software presents a significant challenge for detection and analysis. This insightful guide will teach you how to apply the principles of data science to online security, acting as both an educational resource and a practical manual for everyday use. Data Science for Malware Analysis starts by explaining the nuances of malware, from its lifecycle to its technological aspects before introducing you to the capabilities of data science in malware detection by leveraging machine learning, statistical analytics, and social network analysis. As you progress through the chapters, you’ll explore the analytical methods of reverse engineering, machine language, dynamic scrutiny, and behavioral assessments of malicious software. You’ll also develop an understanding of the evolving cybersecurity compliance landscape with regulations such as GDPR and CCPA, and gain insights into the global efforts in curbing cyber threats. By the end of this book, you’ll have a firm grasp on the modern malware lifecycle and how you can employ data science within cybersecurity to ward off new and evolving threats.

What you will learn

Understand the science behind malware data and its management lifecycle

Explore anomaly detection with signature and heuristics-based methods

Analyze data to uncover relationships between data points and create a network graph

Discover methods for reverse engineering and analyzing malware

Use ML, advanced analytics, and data mining in malware data analysis and detection

Explore practical insights and the future state of AI''s use for malware data science

Understand how NLP AI employs algorithms to analyze text for malware detection

Who this book is for

This book is for cybersecurity experts keen on adopting data-driven defense methods. Data scientists will learn how to apply their skill set to address critical security issues, and compliance officers navigating global regulations like GDPR and CCPA will gain indispensable insights. Academic researchers exploring the intersection of data science and cybersecurity, IT decision-makers overseeing organizational strategy, and tech enthusiasts eager to understand modern cybersecurity will also find plenty of useful information in this guide. A basic understanding of cybersecurity and information technology is a prerequisite.