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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 (14) 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. Other Books You May Enjoy Appendix: Index

Artificial Intelligence for Malware Data Analysis and Detection

The increasing sophistication and frequency of malware attacks pose significant challenges to cybersecurity professionals. Traditional methods of detecting and analyzing malware are often unable to keep up with the evolving threat landscape. Artificial intelligence (AI) has emerged as a powerful tool for malware data analysis and detection, providing more accurate and efficient solutions to combat this growing problem.

This chapter provides an in-depth exploration of AI techniques that are used in malware data analysis, including machine learning and deep learning approaches. This chapter explores the role of AI in malware analysis, its benefits, challenges, and future prospects.

We will cover the following topics in this chapter:

  • AI techniques used in malware data analysis
  • Benefits of AI in malware detection
  • Future prospects
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