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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

Normalcy and anomaly detection

In cybersecurity, the concepts of normalcy and anomaly detection are fundamental for establishing robust protective mechanisms. Normalcy refers to the expected, routine behaviors and operations within a system or network. This understanding of normalcy acts as a reference point for identifying irregularities or suspicious activities. However, the notion of what is considered “normal” is dynamic; it evolves with changes in system configurations, network traffic, and user behaviors. On the other hand, anomaly detection aims to identify deviations from this baseline of normalcy, often indicative of potential security threats such as malware or unauthorized intrusions. Operationalizing anomaly detection involves several key steps: establishing a baseline of normal behavior, continuous monitoring of systems or networks, identifying anomalies, investigating these irregularities for potential threats, initiating appropriate responses if threats...

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