Book Image

Malware Science

By : Shane Molinari
Book Image

Malware Science

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. Malware Science 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 (15 chapters)
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
Appendix

The future state of enhanced sandbox environments in cybersecurity

In the world of cybersecurity, a sandbox typically refers to an isolated computing environment where suspicious programs can be executed to observe their behavior without risking harm to the actual system. This technique is invaluable for analyzing potential malware and understanding its operations and objectives.

Modern challenges – evolving malware tactics

As sandboxes became prevalent tools for threat analysis, malware developers adapted. Modern strains of malware are equipped with sandbox detection techniques, allowing them to identify when they’re being run in an artificial environment. If detected, these malicious programs can alter their behavior, hide their true intentions, or even remain dormant, effectively evading analysis.

This cat-and-mouse game has presented significant challenges:

  • Limitations in emulation: Many sandboxes emulate user activities (for example, mouse movements...