Book Image

Malware Science

By : Shane Molinari
Book Image

Malware Science

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. 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.
Table of Contents (15 chapters)
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
Appendix

The future state of AI ethics and governance standards

As AI becomes more integrated into various aspects of society, including compliance management, there will likely be a push for international AI ethics and governance standards. These standards could address issues such as bias in AI algorithms, transparency, and accountability in AI decision-making, and mechanisms to ensure AI compliance with laws and regulations.

The rise of AI technologies presents both opportunities and challenges for compliance. AI has the potential to revolutionize how businesses manage compliance processes by automating tasks, analyzing complex data, and improving decision-making accuracy. However, alongside these benefits, the deployment of AI introduces ethical considerations and potential risks that need to be carefully managed.

While AI can enhance efficiency and accuracy in compliance processes, it also raises concerns about biases, accountability, and transparency. AI algorithms learn from historical...