Skip to Content
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...

Let's learn how to crack a PUF with ML:

  1. Load a CRP dataset, in this case, CRPDataset.csv:
import pandas as pddf = pd.read_csv("CRPdataset.csv")

The data is made up of pairs (x,y), where x is a binary string that's 64 in length and y is a binary digit. Here, x is a challenge and y is a response.

  1. Convert the pandas dataframe into a NumPy array of features and labels:
y = df.pop("Label").valuesX = df.values
  1. Perform a train-test split:
from sklearn.model_selection import train_test_splitX_train, X_test, y_train, y_test = train_test_split(    X, y, test_size=0.25, random_state=11)
  1. Instantiate and train an XGBoost classifier:
from xgboost import XGBClassifierclf = XGBClassifier()clf.fit(X_train, y_train)print(clf.score(X_train, ...
Become an O’Reilly member and get unlimited access to this title plus top books and audiobooks from O’Reilly and nearly 200 top publishers, thousands of courses curated by job role, 150+ live events each month,
and much more.
Start your free trial

You might also like

Hands-On Machine Learning for Cybersecurity

Hands-On Machine Learning for Cybersecurity

Soma Halder, Sinan Ozdemir
Machine Learning on Kubernetes

Machine Learning on Kubernetes

Faisal Masood, Ross Brigoli

Publisher Resources

ISBN: 9781789614671Supplemental Content