What we think we know about cybersecurity: an investigation of the relationship between perceived knowledge, internet trust, and protection motivation in a cybercrime context. Issue 8 (11th June 2022)

• Record Type: Journal Article
• Authors: De Kimpe, Lies; Walrave, Michel; Verdegem, Pieter; Ponnet, Koen
• Is Part Of: Behaviour & information technology. Volume 41:Issue 8(2022)
• Page Start: 1796
• Page End: 1808
• Publication Date: 2022-06-11
• Subjects: Protection motivation theory -- cybercrime -- optimism bias -- perceived knowledge -- internet trust; Electronic data processing -- Periodicals; Human engineering -- Periodicals; Information technology -- Periodicals; 303.4833
• DOI: 10.1080/0144929X.2021.1905066
• Languages: English
• ISSNs: 0144-929X

Abstract

ABSTRACT: Individual internet users are commonly considered the weakest links in the cybersecurity chain. One reason for this is that they tend to be overoptimistic regarding their own online safety. To gain a better understanding of the cognitive processes involved in this assessment, the current study applies an extended version of the protection motivation theory. More specifically, this study includes perceived knowledge and internet trust to discover how these antecedents influence the threat and coping appraisal processes. Based on representative survey data collected from 967 respondents, we found that people who feel well-informed about online safety feel less vulnerable to cybercrime and are less inclined to take security measures. At the same time, feeling informed is associated with being more convinced of the severity of cybercrime. High levels of trust in the safety of the internet are linked to the feeling that one is less vulnerable to cybercrime and the perception that cybercrime is not a severe threat. Future interventions should remind internet users about their own perceived vulnerability and the risks that exist online while ensuring that internet users do not lose their trust in the internet and confidence in their own online knowledge.