How to create and verify DSA signatures using Python?

by | Jun 9, 2021 | Cryptography And Python, Encryption, Featured

hash.

We are here signing a message using Crypto.Signature.DSS. Using this signature scheme, we can create or verify DSA signatures. We are providing two arguments to the function DSS.new(). The first one is the key pair that has private key components and the second one is the mode. In ‘fips-186-3’ mode, the signature generation is randomized and it follows FIPS 186-3 standards.

The created signature can be sent to a recipient along with the message. The sent signature can then be verified in the following way:

def verify_signature(filename, message, signature1):

    with open(filename, "rb") as file1:
        public_key1 = DSA.importKey(file1.read())

    message_hash = SHA256.new(message.encode())
    verifier = DSS.new(public_key1, 'fips-186-3')

    try:
        verifier.verify(message_hash, signature1)
        print("Verification is successful")
    except ValueError:
        print("Verification failed")

Please note that we are using the private key for creating the DSA signature and the public key for verifying the same signature. At the time of verification also, we are first generating the message hash using the SHA 256 algorithm and then using the message hash for the verification purpose. Here also we are using Crypto.Signature.DSS for signature verification.

The complete code for generating DSA keys, creating DSA signatures, and verifying DSA signatures is given below:

from Crypto.PublicKey import DSA
from Crypto.Hash import SHA256
from Crypto.Signature import DSS


def create_signature(message, filename):

    with open(filename, "rb") as file1:

        private_key = DSA.importKey(file1.read(), 'MyPassphrase')

    message_hash = SHA256.new(message.encode())
    signer = DSS.new(private_key, 'fips-186-3')
    signature1 = signer.sign(message_hash)

    return signature1


def verify_signature(filename, message, signature1):

    with open(filename, "rb") as file1:
        public_key1 = DSA.importKey(file1.read())

    message_hash = SHA256.new(message.encode())
    verifier = DSS.new(public_key1, 'fips-186-3')

    try:
        verifier.verify(message_hash, signature1)
        print("Verification is successful")
    except ValueError:
        print("Verification failed")


keypair = DSA.generate(2048)
public_key = keypair.publickey()

with open("public_key_dsa.pem", "wb") as file:
    file.write(public_key.exportKey('PEM'))
    file.close()

with open("private_key_dsa.pem", "wb") as file:
    file.write(keypair.exportKey('PEM', True, 'MyPassphrase'))
    file.close()

text = "Secret Message"

signature = create_signature(text, 'private_key_dsa.pem')
print(signature)
verify_signature('public_key_dsa.pem', text, signature)

Interested readers who want to know more on how to implement the DSA algorithm in Python, please refer to the following articles:

How to implement the DSA key generation algorithm in Python?
How to implement the DSA signature creation and verification algorithm in Python?

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 »