<abstract xmlns="http://www.w3.org/1999/xhtml">

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

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

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

Cybernetics and Information Technologies

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

{"article-title":"Enhancеd Analysis Approach to Detect Phishing Attacks During COVID-19 Crisis"}

Public health responses to the COVID-19 pandemic since March 2020 have led to lockdowns and social distancing in most countries around the world, with a shift...

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

Online veröffentlicht: 10. Apr. 2022

Seitenbereich: 60 - 76

Eingereicht: 29. Dez. 2021

Akzeptiert: 22. Feb. 2022

DOI: https://doi.org/10.2478/cait-2022-0004

Schlüsselwörter
Cybersecurity, COVID-19, phishing attack, cybercrime

© 2022 Mousa Tayseer Jafar et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

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

Online veröffentlicht: 10. Apr. 2022

Seitenbereich: 60 - 76

Eingereicht: 29. Dez. 2021

Akzeptiert: 22. Feb. 2022

DOI: https://doi.org/10.2478/cait-2022-0004

SchlüsselwörterCybersecurity, COVID-19, phishing attack, cybercrime

© 2022 Mousa Tayseer Jafar et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Schlüsselwörter
Cybersecurity, COVID-19, phishing attack, cybercrime