Enhancеd Analysis Approach to Detect Phishing Attacks During COVID-19 Crisis

Abstract Public health responses to the COVID-19 pandemic since March 2020 have led lockdowns and social distancing in most countries around world, with a shift from traditional work environment virtual one. Employees been encouraged home where possible slow down viral infection. The massive increase volume of professional activities executed online has posed new context for cybercrime, number emails phishing websites. Phishing attacks broadened extended through years pandemics COVID-19. This paper presents novel approach detecting Uniform Resource Locators (URLs) applying Gated Recurrent Unit (GRU), fast highly accurate classifier system. Comparative analysis GRU classification system indicates better accuracy (98.30%) than other systems.