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

Benefits of AI in malware detection

Navigating the realm of malware detection, AI technologies bring forth pronounced advantages. In this section, we’ll delve into how AI enhances detection accuracy, amplifying the precision of malware detection systems. Then, we’ll discuss real-time threat monitoring, highlighting how AI facilitates continuous scrutiny and rapid response to threats. Lastly, we’ll spotlight AI’s role in achieving scalability and efficiency, enabling organizations to process vast data volumes effectively. Each section will underscore the transformative benefits of AI in malware detection methodologies.

Enhanced detection accuracy

AI techniques offer significant advantages in the field of malware detection, with enhanced detection accuracy being a primary benefit. Leveraging AI algorithms and models can greatly improve the accuracy and effectiveness of malware detection systems. Here are the key factors that contribute to enhanced detection...