Cryptography Book: The Design And Implementation Of DSA And ECDSA Using Python

The Design And Implementation Of DSA And ECDSA Using Python

About The Book

The book “The Design And Implementation Of DSA And ECDSA Using Python” discusses the design of the DSA and ECDSA algorithms. The book also discusses the implementation of the DSA and ECDSA algorithms using Python without using any Python library dedicated to them.

The book is divided into 17 chapters. The first ten chapters discuss the mathematical concepts required to understand the design and implementation of DSA and ECDSA. Chapters 11 and 12 discuss what digital signatures are, how they work, and the Digital Signature Algorithm (DSA).

Chapter 13 discusses implementing DSA using Python libraries. Chapters 14 and 15 discuss implementing the DSA algorithm using Python without using any Python library dedicated to DSA.

Chapter 16 provides a basic introduction to elliptic curve cryptography without understanding which understanding ECDSA is difficult. Chapter 17 discusses the ECDSA algorithm and how to implement it using Python without using any Python library dedicated to ECDSA.

The book explains all the mathematical concepts crucial for understanding the design and implementation of DSA and ECDSA. Any reader with some knowledge of Python can benefit from the book.

About The Author

Ms. Amrita Mitra is an author and security researcher. Her areas of interest are cyber security, Artificial Intelligence, and mathematics. She is also an entrepreneur who spreads knowledge and awareness about cyber security and Artificial Intelligence through her website, The Security Buddy.

How To Buy The Book

The book is available on Amazon, both in paperback and Kindle format.

Reviews and Comments

If you have read the cryptography book and want to give your valuable reviews, comments, or feedback, please do so on Amazon. We will be more than happy to receive comments, feedback, and suggestions from our readers.

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...

Not a premium member yet?

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

Featured Posts

Translate »