An epidemiological model for computer virus with Atangana–Baleanu fractional derivative

Abstract

The Era of data is transubstantiating into a Big Data model in this technological world in the early 21st century. In 2005, Roger Mougalas coined a combination of data for this future world of the human race. The information helps to find specific solutions for any physical problem under Catastrophic circumstances in high populations such as Covid-19. To store massive data and historical events in a computer, the possibility of damage occurred to the complete data. Hence, viruses are a crucial threat to such data worth millions and billions. For this purpose, we spend enormous costs and efforts to build defensive strategies to save that information. Analyzing the expansion and extension of viruses helps to protect data and prevent viruses. In this manuscript, we study optimal control analysis for the suggested model in the sense of the Atangana–Baleanu derivative (AB-derivative). We employed a fixed point theorem to analyze the solutions for the fractional order computer virus model. We verified the results numerically and expressed them graphically.