Developing an algorithm for the application of Bayesian method to software using artificial immune systems

Shafagat Mahmudova

doi:10.1007/s00500-021-05972-2

Abstract

This paper develops a new algorithm by applying the Bayesian method to software using artificial immune systems. An artificial immune system is an adaptive computing system that uses models, principles, mechanisms, and functions used to solve problems in theoretical immunology. Its application to various fields of science is studied. The role that artificial immune systems play in software is invaluable. Methods for detecting malware are explored. Some works in the field of artificial immune system are analyzed and issues to be addressed are identified. The Bayesian method accurately calculates the probability of occurrence of any event under certain conditions. Therefore, the Bayesian method is applied to software using artificial immune systems. By applying this method, fast software performance can be achieved. For this, a new algorithm is developed and experiments are conducted. The developed algorithm is one of the new ones. The results of the experiments provide good performance.

Highlights

The expansion of information technology has led to the development of many fields of science
The interdisciplinary field of Artificial Intelligence (AI) is quite broad and includes many sciences and professions, including computer science, psychology, linguistics, philosophy, neurology, and so on. This area was built on the idea of Homo Sapiens as a central intellectual property of people "that an intelligent can describe the mind so precisely that a machine can be created to model it." AI has been a subject of great optimism; it has surprisingly failed (Sniecinski et al 2018)
These methods alter the syntax of the program without changing its semantics, making it more difficult to analyze and comprehend malicious codes (Venkatesan 2008). This can be achieved by changing the registers where the variables are placed, but the program code remains unchanged; it changes the rules of execution of processes dealing with other harmful instructions with exchange instructions, etc

Summary

Introduction

The expansion of information technology has led to the development of many fields of science. The technologies based on the working principles of the human body have gained wide popularity: artificial intelligence, visual processing tools, artificial retina, all types of genetic algorithms and so on. The technology based on the same principles as a human body is widely used: the neural networks based on artificial intelligence, visual image processing, artificial retina, and various genetic algorithms. Artificial immune systems mainly use on type of artificial intelligence to protect against computer viruses, to detect network interventions, and so on. Another process arises where the natural selection of antibodies occurs during clonal selection: survival of only those who live under the identified external body. Such algorithms use the memory and learning capability of the immune system to solve the problem

Related Works

Methods for malware detection

Development of an algorithm using Bayesian method

Conclusion