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Data Science for Malware Analysis

Data Science for Malware Analysis

By : Shane Molinari
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Data Science for Malware Analysis

Data Science for Malware Analysis

4 (4)
By: Shane Molinari

Overview of this book

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.
Table of Contents (14 chapters)
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1
Part 1– Introduction
Free Chapter
2
Chapter 1: Malware Science Life Cycle Overview
4
Part 2 – The Current State of Key Malware Science AI Technologies
8
Part 3 – The Future State of AI’s Use for Malware Science
11
Chapter 8: Epilogue – A Harmonious Overture to the Future of Malware Science and Cybersecurity

Preface

In an age where our digital lives are expanding at an unprecedented pace, cybersecurity is a growing concern. Malware is more than a fleeting nuisance; it’s a complex field requiring a nuanced, multi-layered defense strategy.

This book sits at the intersection of cybersecurity and data science, offering a comprehensive guide to understanding and combating malware. Drawing from my 20+ years of experience in military and civilian cyber-threat management, I aim to make this complex subject matter accessible to cybersecurity professionals and data science enthusiasts alike.

The book comprises seven focused chapters and an epilogue, each contributing to a multi-faceted understanding of malware.

The examples and case studies peppered throughout are designed for real-world application, aiming to arm you with the knowledge and tools to enhance your cyber resilience.

I owe a debt of gratitude to my industry peers and the many researchers whose work forms the foundation of this book. Their critiques and encouragement have been invaluable.

Whether you are a seasoned cybersecurity expert, a student of data science, or someone who is keen to understand modern digital threats, this book aims to serve as a practical guide.

Thank you for investing your time in reading Data Science for Malware Analysis. Together, let’s build a safer digital future.

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