Data Science for Malware Analysis: A comprehensive guide to using AI in detection, analysis, and compliance - Softcover

Shane Molinari

Softcover

ISBN 10: 1804618640 ISBN 13: 9781804618646

Publisher: Packt Publishing, 2023

Synopsis

Unlock the secrets of malware data science with cutting-edge techniques, AI-driven analysis, and international compliance standards to stay ahead of the ever-evolving cyber threat landscape

Key Features

• Get introduced to three primary AI tactics used in malware and detection
• Leverage data science tools to combat critical cyber threats
• Understand regulatory requirements for using AI in cyber threat management
• Purchase of the print or Kindle book includes a free PDF eBook

Book Description

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.

What you will learn

• Understand the science behind malware data and its management lifecycle
• Explore anomaly detection with signature and heuristics-based methods
• Analyze data to uncover relationships between data points and create a network graph
• Discover methods for reverse engineering and analyzing malware
• Use ML, advanced analytics, and data mining in malware data analysis and detection
• Explore practical insights and the future state of AI's use for malware data science
• Understand how NLP AI employs algorithms to analyze text for malware detection

Who this book is for

This book is for cybersecurity experts keen on adopting data-driven defense methods. Data scientists will learn how to apply their skill set to address critical security issues, and compliance officers navigating global regulations like GDPR and CCPA will gain indispensable insights. Academic researchers exploring the intersection of data science and cybersecurity, IT decision-makers overseeing organizational strategy, and tech enthusiasts eager to understand modern cybersecurity will also find plenty of useful information in this guide. A basic understanding of cybersecurity and information technology is a prerequisite.

Table of Contents

1. Malware Data Science Life Cycle Overview
2. An Overview of the International History of Cyber Malware Impacts
3. Topological Data Analysis for Malware Detection and Analysis
4. Artificial Intelligence for Malware Data Analysis and Detection
5. Behavior-Based Malware Data Analysis and Detection
6. The Future State of Malware Data Analysis and Detection
7. The Future State of Key International Compliance Requirements
8. Epilogue – A Harmonious Overture to the Future of Malware Data Science and Cybersecurity

About this title

About the Author

Shane Molinari is a cyber-threat management veteran with over 20 years of experience in military, Department of Defense, and civilian sectors. As an authority in the cyber-risk industry, he brings a nuanced understanding of data science's role in combating malware. Shane holds degrees focusing on Engineering and Systems Design, respectively. A Certified Information Systems Security Professional (CISSP), he's penned thought leadership articles and has been a featured speaker in cybersecurity podcasts. His diverse experience spans from implementing business continuity programs to advising Fortune 500 companies on navigating data privacy regulations like GDPR and CCPA. This book is an amalgamation of Shane's in-depth knowledge in data science applications and malware defense techniques, designed to serve as a practical manual for bolstering day-to-day cyber resilience.

From the Back Cover

Unlock the secrets of malware data science with cutting-edge techniques, AI-driven analysis, and international compliance standards to stay ahead of the ever-evolving cyber threat landscapeKey FeaturesGet introduced to three primary AI tactics used in malware and detection Leverage data science tools to combat critical cyber threats Understand regulatory requirements for using AI in cyber threat management Purchase of the print or Kindle book includes a free PDF eBook Book Description 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.What you will learnUnderstand the science behind malware data and its management lifecycle Explore anomaly detection with signature and heuristics-based methods Analyze data to uncover relationships between data points and create a network graph Discover methods for reverse engineering and analyzing malware Use ML, advanced analytics, and data mining in malware data analysis and detection Explore practical insights and the future state of AI's use for malware data science Understand how NLP AI employs algorithms to analyze text for malware detection Who this book is for This book is for cybersecurity experts keen on adopting data-driven defense methods. Data scientists will learn how to apply their skill set to address critical security issues, and compliance officers navigating global regulations like GDPR and CCPA will gain indispensable insights. Academic researchers exploring the intersection of data science and cybersecurity, IT decision-makers overseeing organizational strategy, and tech enthusiasts eager to understand modern cybersecurity will also find plenty of useful information in this guide. A basic understanding of cybersecurity and information technology is a prerequisite.Table of ContentsMalware Data Science Life Cycle Overview An Overview of the International History of Cyber Malware Impacts Topological Data Analysis for Malware Detection and Analysis Artificial Intelligence for Malware Data Analysis and Detection Behavior-Based Malware Data Analysis and Detection The Future State of Malware Data Analysis and Detection The Future State of Key International Compliance Requirements Epilogue - A Harmonious Overture to the Future of Malware Data Science and Cybersecurity

Edition details

• Publisher: Packt Publishing
• Publication date: 2023
• Language: English
• ISBN 10: 1804618640
• ISBN 13: 9781804618646
• Binding: Paperback
• Number of pages: 230