What is the One Time Pad in cryptography?

by | Jul 12, 2021 | Cryptography And Python, Encryption, Information Security

In cryptography, the One Time Pad is an encryption technique in which a secret key of length more than or equal to that of the plaintext message is used to encrypt the message. The secret key is randomly generated and it is pre-shared with the communicating parties. The secret key is then combined with the plaintext message to generate the ciphertext.

The ciphertext thus generated is information-theoretically secure provided the following conditions are met:

  • The key is randomly generated.
  • The length of the key is not less than the length of the plaintext message.
  • No part of the key is re-used.
  • The key is kept secret by the communicating parties.

Let’s look at an example. Let’s say Alice wants to send a secret message to Bob. The secret message is “attack.” Alice uses a randomly generated secret key “dtekwr.” The length of the secret key is the same as the length of the plaintext message and Alice ensures that the key is randomly generated and no part of the key is re-used. Alice then combines each character of the key with each character of the plaintext message. Let’s say addition modulo 26 is used.

So, ‘a’ will be added modulo 26 with ‘d’ or ‘3’. The first ‘t’ will be added modulo 26 with ‘t’ or 19 and so on.

Plaintext:     a(0)    t(19)    t(19)    a(0)   c(2)   k(10)
Key:           d(3)    t(19)    e(4)     k(10)  w(22)  r(17)
Ciphertext:    d(3)    m(12)    x(23)    k(10)  y(24)  b(1)

Hence, the ciphertext will be “dmxkyb.”

Using information theory, Claude Shannon proved that the One Time Pad has a property called perfect secrecy. As the key is randomly generated, has a length more than or equal to that of the plaintext message, the key is not re-used in whole or in part and the key is kept secure by the communicating parties, the generated ciphertext provides no additional information about the plaintext. Hence, the one-time pad is secure even if an adversary has infinite computational power.

But, in practical scenario, One Time Pads have the following problems:

1. The key should be truly random and not a pseudo-random value generated using a pseudo-random number generator.
2. The randomly generated key should have a length more than or equal to that of the plaintext message and no part of the key should be re-used. Moreover, the key should be kept secure by the communicating parties and after the use, the key should be disposed of correctly to ensure the key is never reused in whole or in part.

One Time Pads are mimicked by stream ciphers in practical applications.

I hope this helps. However, readers who want to know more about how different cryptographic algorithms work and how they are used in various secure network protocols can refer to the book “Cryptography And Public Key Infrastructure.”

Facebooktwitterredditpinterestlinkedinmail

Calculate the pseudoinverse of a matrix using Python

What is the pseudoinverse of a matrix? We know that if A is a square matrix with full rank, then A-1 is said to be the inverse of A if the following condition holds: $latex AA^{-1}=A^{-1}A=I $ The pseudoinverse or the Moore-Penrose inverse of a matrix is a...

Cholesky decomposition using Python

What is Cholesky decomposition? A square matrix A is said to have Cholesky decomposition if it can be written as a product of a lower triangular matrix and its conjugate transpose. $latex A=LL^{*} $ If all the entries of A are real numbers, then the conjugate...

Tensor Hadamard Product using Python

In one of our previous articles, we already discussed what the Hadamard product in linear algebra is. We discussed that if A and B are two matrices of size mxn, then the Hadamard product of A and B is another mxn matrix C such that: $latex H_{i,j}=A_{i,j} \times...

Perform tensor addition and subtraction using Python

We can use numpy nd-array to create a tensor in Python. We can use the following Python code to perform tensor addition and subtraction. import numpy A = numpy.random.randint(low=1, high=10, size=(3, 3, 3)) B = numpy.random.randint(low=1, high=10, size=(3, 3, 3)) C =...

How to create a tensor using Python?

What is a tensor? A tensor is a generalization of vectors and matrices. It is easily understood as a multidimensional array. For example, in machine learning, we can organize data in an m-way array and refer it as a data tensor. Data related to images, sounds, movies,...

How to combine NumPy arrays using horizontal stack?

We can use the hstack() function from the numpy module to combine two or more NumPy arrays horizontally. For example, we can use the following Python code to combine three NumPy arrays horizontally. import numpy A = numpy.array([[1, 2, 3], [4, 5, 6], [7, 8, 9]]) B =...

How to combine NumPy arrays using vertical stack?

Let’s say we have two or more NumPy arrays. We can combine these NumPy arrays vertically using the vstack() function from the numpy module. For example, we can use the following Python code to combine three NumPy arrays vertically. import numpy A = numpy.array([[1, 2,...

Singular Value Decomposition (SVD) using Python

What is Singular Value Decomposition (SVD)? Let A be an mxn rectangular matrix. Using Singular Value Decomposition (SVD), we can decompose the matrix A in the following way: $latex A_{m \times n}=U_{m \times m}S_{m \times n}V_{n \times n}^T $ Here, U is an mxm matrix....

Eigen decomposition of a square matrix using Python

Let A be a square matrix. Let’s say A has k eigenvalues λ1, λ2, ... λk. And the corresponding eigenvectors are X1, X2, ... Xk. $latex X_1=\begin{bmatrix} x_{11} \\ x_{21} \\ x_{31} \\ ... \\ x_{k1} \end{bmatrix} \\ X_2=\begin{bmatrix} x_{12} \\ x_{22} \\ x_{32} \\ ......

How to calculate eigenvalues and eigenvectors using Python?

In our previous article, we discussed what eigen values and eigenvectors of a square matrix are and how we can calculate the eigenvalues and eigenvectors of a square matrix mathematically. We discussed that if A is a square matrix, then $latex (A- \lambda I) \vec{u}=0...

Amrita Mitra

Author

Ms. Amrita Mitra is an author, who has authored the books “Cryptography And Public Key Infrastructure“, “Web Application Vulnerabilities And Prevention“, “A Guide To Cyber Security” and “Phishing: Detection, Analysis And Prevention“. She is also the founder of Asigosec Technologies, the company that owns The Security Buddy.

0 Comments

Submit a Comment

This site uses Akismet to reduce spam. Learn how your comment data is processed.

Not a premium member yet?

Please follow the link below to buy The Security Buddy Premium Membership.

Featured Posts

Translate »