Genetic Algorithm Powered Bivariate Function Encryption for Robust Data Security
N.R. Hariharan, R.Sai Ritheshwar, R. Suseendran, R. Meena, T. Kalaiselvi · 2025
This paper introduces a new encryption technique which bases its operations on advanced bivariate mathematical functions and uses a genetic algorithm to optimize these along with random key generation techniques. This, in turn, allows for the enhancement of cryptographic complexity and better security features with fortified protection against any possible attacks. The encryption mechanism integrates random keys along with the evolved bivariate functions, and RSA protocol is employed for securing the channel of exchanging keys, ensuring confidentiality at each stage of the transmission process. The integration of these methodologies has created a two-layer security framework that combines the efficiency of symmetric encryption with the robustness of RSA. Advanced symmetric encryption combined with RSA significantly increases the security measures provided by defending against brute force attacks, cryptanalysis, and intercept threats. Through the combination of symmetric encryption and an asymmetric key exchange protocol, this strategy fully addresses the disadvantages of the typical cryptographic system. It forms an effective solution in meeting the contemporary security demands for digital communication environments.