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Machine Learning for Cybersecurity Cookbook
book

Machine Learning for Cybersecurity Cookbook

by Emmanuel Tsukerman
November 2019
Intermediate to advanced content levelIntermediate to advanced
346 pages
9h 36m
English
Packt Publishing
Content preview from Machine Learning for Cybersecurity Cookbook

How to do it...

In the following steps, we will demonstrate how a binary classifier can detect obfuscated JavaScript files:

  1. Begin by importing the libraries we will be needing to process the JavaScript's content, prepare the dataset, classify it, and measure the performance of our classifier:
import osfrom sklearn.feature_extraction.text import HashingVectorizer, TfidfTransformerfrom sklearn.ensemble import RandomForestClassifierfrom sklearn.model_selection import train_test_splitfrom sklearn.metrics import accuracy_score, confusion_matrixfrom sklearn.pipeline import Pipeline
  1. We specify the paths of our obfuscated and non-obfuscated JavaScript files and assign the two types of file different labels:
js_path = "path\\to\\JavascriptSamples" ...
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Publisher Resources

ISBN: 9781789614671Supplemental Content