MW Mkaouer
Effects of COVID-19 pandemic on computational intelligence and cybersecurity: survey
Mkaouer, MW; Gaber, TMA; Dagdia, ZC
Authors
TMA Gaber
ZC Dagdia
Abstract
In late December 2019, the World Health Organization (WHO) announced the outbreak of a new type of coronavirus, named the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), also known as COVID-19. The deadliness of the virus has forced governments and countries to socially isolate their populations, causing a worldwide impact on the economy. Pandemic management has stressed health systems to work beyond their limits, adding more to the tragedy of losing millions of lives. As a natural response to such disasters, intelligent systems have been developed for various reasons related to virus detection, tracking and control. The social lockdown created a record level of online platforms and applications being used to resume professional and educational activities in a virtual environment. This has triggered an unprecedented growth in cybercrime. This paper presents the effects of the pandemic on computational intelligence and cybersecurity.</p></abstract>
Citation
Mkaouer, M., Gaber, T., & Dagdia, Z. (2022). Effects of COVID-19 pandemic on computational intelligence and cybersecurity: survey. Applied Computational Intelligence and Soft Computing, 2(2), 173-194. https://doi.org/10.3934/aci.2022010
Journal Article Type | Article |
---|---|
Acceptance Date | Nov 1, 2022 |
Publication Date | Nov 17, 2022 |
Deposit Date | Dec 7, 2022 |
Publicly Available Date | Dec 7, 2022 |
Journal | Applied Computing and Intelligence |
Print ISSN | 1687-9724 |
Electronic ISSN | 1687-9732 |
Publisher | Hindawi |
Volume | 2 |
Issue | 2 |
Pages | 173-194 |
DOI | https://doi.org/10.3934/aci.2022010 |
Publisher URL | https://doi.org/10.3934/aci.2022010 |
Files
Published Version
(880 Kb)
PDF
Licence
http://creativecommons.org/licenses/by/4.0/
Publisher Licence URL
http://creativecommons.org/licenses/by/4.0/
You might also like
Deep churn prediction method for telecommunication industry
(2023)
Journal Article
Optimized and efficient image-based IoT malware detection method
(2023)
Journal Article
Downloadable Citations
About USIR
Administrator e-mail: library-research@salford.ac.uk
This application uses the following open-source libraries:
SheetJS Community Edition
Apache License Version 2.0 (http://www.apache.org/licenses/)
PDF.js
Apache License Version 2.0 (http://www.apache.org/licenses/)
Font Awesome
SIL OFL 1.1 (http://scripts.sil.org/OFL)
MIT License (http://opensource.org/licenses/mit-license.html)
CC BY 3.0 ( http://creativecommons.org/licenses/by/3.0/)
Powered by Worktribe © 2025
Advanced Search