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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 collect notable portions of the PE header:

  1. Import pefile and modules for enumerating our samples:
import pefilefrom os import listdirfrom os.path import isfile, joindirectories = ["Benign PE Samples", "Malicious PE Samples"]
  1. We define a function to collect the names of the sections of a file and preprocess them for readability and normalization:
def get_section_names(pe):    """Gets a list of section names from a PE file."""    list_of_section_names = []    for sec in pe.sections:        normalized_name = sec.Name.decode().replace("\x00", "").lower()        list_of_section_names.append(normalized_name)    return list_of_section_names
  1. We define a convenience function to preprocess and standardize our imports:
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Publisher Resources

ISBN: 9781789614671Supplemental Content