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Data Science for Malware Analysis

You're reading from   Data Science for Malware Analysis A comprehensive guide to using AI in detection, analysis, and compliance

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Product type Paperback
Published in Dec 2023
Publisher Packt
ISBN-13 9781804618646
Length 230 pages
Edition 1st Edition
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Author (1):
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Shane Molinari Shane Molinari
Author Profile Icon Shane Molinari
Shane Molinari
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Table of Contents (15) Chapters Close

Preface 1. Part 1– Introduction
2. Chapter 1: Malware Science Life Cycle Overview FREE CHAPTER 3. Chapter 2: An Overview of the International History of Cyber Malware Impacts 4. Part 2 – The Current State of Key Malware Science AI Technologies
5. Chapter 3: Topological Data Analysis for Malware Detection and Analysis 6. Chapter 4: Artificial Intelligence for Malware Data Analysis and Detection 7. Chapter 5: Behavior-Based Malware Data Analysis and Detection 8. Part 3 – The Future State of AI’s Use for Malware Science
9. Chapter 6: The Future State of Malware Data Analysis and Detection 10. Chapter 7: The Future State of Key International Compliance Requirements 11. Chapter 8: Epilogue – A Harmonious Overture to the Future of Malware Science and Cybersecurity
12. Index 13. Other Books You May Enjoy Appendix

The future state of deeper OS-level integrations in malware detection

The cybersecurity landscape is in a perpetual state of flux. As technology becomes more ingrained in our daily lives, the avenues for malicious cyberattacks expand in tandem. At the core of almost every device we use is the OS, a critical piece of software that manages hardware resources and provides services for computer programs. With the evolving threat matrix, the need to bolster defenses at the very nucleus of our devices – the OS – becomes even more pressing. The future of malware detection, thus, seems inevitably tied to deeper OS-level integrations.

The current state of malware detection

Traditional malware detection methods have revolved around signature-based techniques. These rely on known patterns or “signatures” of malware. When a piece of software or a file matches this signature, it’s flagged as malicious. While effective against known threats, this method struggles...

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