Protection against cyber attacks using the El-Gamal cryptosystem using artificial intelligence technologies

Abstract

The article is devoted to the development of an efficient digital decryption scheme in the ElGamal cryptosystem using the extended Euclidean algorithm to solve the linear Diophantine equation. Based on the problem of constructing a scheme that takes into account the use of multi-digit numbers in cryptography, the relevance of encryption and decryption of the El-Gamal public key cryptosystem is considered. When decrypting the ElGamal cryptosystem, the encrypted data was calculated directly from a separate solution of the linear Diophantine equation, without finding the inverse value s^(-1)=C_1^x mod p. Based on this, machine learning was implemented using the linear regression method, selecting 100 data sets generated by decryption in the El-Gamal cryptosystem using the extended Euclidean algorithm. The ability of artificial intelligence to analyze and process information in real time can reduce response time to cyber attacks. This allows organizations to minimize potential losses and improve the effectiveness of security measures.