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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 train a random forest classifier to detect DDoS traffic:

  1. Import pandas and specify the data types for the columns you will be reading in the code:
import pandas as pdfeatures = [    "Fwd Seg Size Min",    "Init Bwd Win Byts",    "Init Fwd Win Byts",    "Fwd Seg Size Min",    "Fwd Pkt Len Mean",    "Fwd Seg Size Avg",    "Label",    "Timestamp",]dtypes = {    "Fwd Pkt Len Mean": "float",    "Fwd Seg Size Avg": "float",    "Init Fwd Win Byts": "int",    "Init Bwd Win Byts": "int",    "Fwd Seg Size Min": "int",    "Label": "str",}date_columns = ["Timestamp"]
  1. Read in the .csv file containing the dataset:
df = pd.read_csv("ddos_dataset.csv", usecols=features, dtype=dtypes,parse_dates=date_columns,index_col=None)
  1. Sort the data by date: ...
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Publisher Resources

ISBN: 9781789614671Supplemental Content