EconPapers    
Economics at your fingertips  
 

A multi-level influence model of COVID-19 themed cybercrime

Rennie Naidoo

European Journal of Information Systems, 2020, vol. 29, issue 3, 306-321

Abstract: The recent severity and frequency of cybercrime has been dominated by a single theme – the COVID-19 pandemic. This research develops a multi-level influence model to explore how cybercriminals are exploiting the COVID-19 pandemic by assessing situational factors, identifying victims, impersonating trusted sources, selecting attack methods, and employing social engineering techniques. The model extends upon prior work on influence techniques and emotional appeals that cybercriminals employ, by bringing into sharper focus the role of situational factors in COVID-19 related cybercrime attacks. Content and thematic analysis was conducted on 185 distinct COVID-19 cybercrime scam incident documents, including text, images, and photos, provided by a global online fraud and cybersecurity company tracking COVID-19 related cybercrime. The analysis reveals interesting patterns about the sheer breadth and diversity of COVID-19 related cybercrime and how these crimes are continually evolving in response to changing situational factors. It is hoped that these insights and recommendations for end-users and organisations can contribute to a safer digital world as we cope with many other pressing challenges during the COVID-19 pandemic.

Date: 2020
References: Add references at CitEc
Citations: View citations in EconPapers (4)

Downloads: (external link)
http://hdl.handle.net/10.1080/0960085X.2020.1771222 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:taf:tjisxx:v:29:y:2020:i:3:p:306-321

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/tjis20

DOI: 10.1080/0960085X.2020.1771222

Access Statistics for this article

European Journal of Information Systems is currently edited by Par Agerfalk

More articles in European Journal of Information Systems from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().

 
Page updated 2025-03-20
Handle: RePEc:taf:tjisxx:v:29:y:2020:i:3:p:306-321