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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 enumerate all the 4-grams of a sample file and select the 50 most frequent ones:

  1. We begin by importing the collections library to facilitate counting and the ngrams library from nltk to ease extraction of N-grams:
import collectionsfrom nltk import ngrams
  1. We specify which file we would like to analyze:
file_to_analyze = "python-3.7.2-amd64.exe"
  1. We define a convenience function to read in a file's bytes:
def read_file(file_path):    """Reads in the binary sequence of a binary file."""    with open(file_path, "rb") as binary_file:        data = binary_file.read()    return data
  1. We write a convenience function to take a byte sequence and obtain N-grams:
def byte_sequence_to_Ngrams(byte_sequence, N): """Creates ...
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Publisher Resources

ISBN: 9781789614671Supplemental Content