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Data Science for Malware Analysis

Data Science for Malware Analysis

By : Shane Molinari
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Data Science for Malware Analysis

Data Science for Malware Analysis

4 (4)
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. Data Science for Malware Analysis 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 (14 chapters)
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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

Behavior-Based Malware Data Analysis and Detection

Behavior-based malware data analysis and detection is a subset of computer security that revolves around detecting and preventing malicious software (malware) based on its behavior or activity, rather than relying on pre-existing, known malware signatures. It represents a more dynamic approach to cybersecurity that goes beyond static defenses as it’s capable of identifying unknown threats that might be missed by traditional antivirus solutions.

In the increasingly complex world of digital technologies, growing cyber threats necessitate the adoption of advanced and comprehensive cybersecurity strategies. A pivotal part of these strategies is behavior-based malware analysis and detection, a proactive method that focuses on software behavior rather than its code structure. This approach has revolutionized malware detection and mitigation, but it’s not a mere plug-and-play solution. Its implementation demands a significant...

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