Comparative Analysis of Artificial Neural Network Statistical Parameters and Novel Techniques for Data Encryption and Decryption, Distribution, and Estimation

Abstract

The use of statistical metrics to compare the application of several unique communication techniques that rely on a certain system is the foundation of this paper. By making it more difficult for attackers to anticipate patterns and the speed of the encryption and decryption processes, this technology protects communication routes. When compared to solutions using mathematical techniques, the employment of artificial neural networks (ANN) in data encryption and decryption, such as communications, demonstrates that the test patterns of cryptographic messages in our collection displayed a shorter decryption time. This study's methodology can be successfully applied to lengthy communications, where it is difficult and time-consuming to apply mathematical methods for encryption and decryption. We present various measures of fitting goodness to the ANN method in order to reach the most preferred distribution to analyses our results, along with the benefits and drawbacks of both approaches in terms of security level, encryption and decryption time, and speed of use.