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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…

  1. Import the random library and select a large prime number, P:
import randomP = 67280421310721
  1. Define an encryption function for three parties:
def encrypt(x):    """Encrypts an integer between 3 partires."""    share_a = random.randint(0, P)    share_b = random.randint(0, P)    share_c = (x - share_a - share_b) % P    return (share_a, share_b, share_c)
  1. Encrypt a numerical variable:
x = 17share_a, share_b, share_c = encrypt(x)print(share_a, share_b, share_c)16821756678516 13110264723730 37348399908492
  1. Define a function to decrypt, given the three shares:
def decrypt(share_a, share_b, share_c):    """Decrypts the integer from 3 shares."""    return (share_a + share_b + share_c) % P
  1. Decrypt the encrypted variable x:
decrypt(share_a, share_b, ...
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Publisher Resources

ISBN: 9781789614671Supplemental Content