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Malware Data Science Reading Diary / Notes

License: MIT License

Python 3.03% Jupyter Notebook 96.97%
malware malware-analysis data-science deep-learning pefile malwareanalysis machine-learning

malwaredatascience's Introduction

Malware Data Science - Reading Diary

This repository contains my take-aways, coding projects and thoughts from the book Malware Data Science by Joshua Saxe and Hillary Sanders. The book was published by the no starch press in fall 2018 and deals with analyzing malware with the help of data science methods.

The Cover of the book

For every chapter, I provide a small summary and for the most chapters I also provide some short codesnippet or jupyter notebook which I worked on to deepen my understanding of the topic. There are the following chapters:

  1. Basic Static Malware Analysis
  2. Beyond Basic Static Analysis: X86 Disassembly
  3. A Brief Introduction to Dynamic Analysis
  4. Identifying Attack Campaigns Using Malware Networks
  5. Shared Code Analysis
  6. Understanding Machine Learning-Based Malware Detectors (You can read this chapter for free here)
  7. Evaluating Malware Detection Systems
  8. Building Machine Learning Detectors
  9. Visualizing Malware Trends
  10. Deep Learning Basics
  11. Building A Neural Network Malware Detector With Keras
  12. Becoming a Data Scientist + My personal résumé

You can get the book here and you can find the corresponding book website here.

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