Environmental Uncertainty and End-User Security Behaviour: A Study During the COVID-19 Pandemic

This dataset contains PLS and Bootstrapping Data.

The COVID-19 pandemic has forced individuals to adopt online applications and technologies, as well as remote working patterns.  However, with changes in technology and working patterns, new  vulnerabilities are likely to arise. Cybersecurity threats have rapidly evolved to exploit uncertainty during the pandemic, and users need to apply careful judgment and vigilance to avoid becoming the victim of a  cyber-attack. This paper explores the factors that motivate security  behaviour, considering the current environmental uncertainty. An adapted  model, primarily based on the Protection Motivation Theory (PMT), is  proposed and evaluated using data collected from an online survey of 222  respondents from a Higher Education institution. Data analysis was  performed using Partial Least Squares Structural Equation Modelling  (PLS-SEM). The results confirm the applicability of PMT in the security  context. Respondents’ behavioural intention, perceived threat  vulnerability, response cost, response efficacy, security habits, and  subjective norm predicted self-reported security behaviour. In contrast,  environmental uncertainty, attitude towards policy compliance,  self-efficacy and perceived threat severity did not significantly impact  behavioural intention. The results show that respondents were able to  cope with environmental uncertainty and maintain security behaviour.

本数据集包含偏最小二乘法（PLS）和自举（Bootstrapping）数据。新冠疫情的爆发迫使个人采纳在线应用程序和技术，以及远程工作模式。然而，随着技术和工作模式的变化，新的脆弱性可能随之产生。网络安全威胁在疫情期间迅速演变，以利用不确定性，用户需谨慎判断并保持警惕，以避免成为网络攻击的受害者。本文探讨了在当前环境不确定性背景下，促使安全行为的因素，并提出了一种基于保护动机理论（PMT）的改进模型，并利用从一所高等教育机构222名受访者进行的在线调查收集的数据进行评估。数据分析采用偏最小二乘结构方程模型（PLS-SEM）进行。结果显示，PMT在安全领域的适用性。受访者的行为意图、感知威胁脆弱性、响应成本、响应效能、安全习惯和主观规范预测了自我报告的安全行为。相比之下，环境不确定性、对政策合规的态度、自我效能感和感知威胁严重性对行为意图没有产生显著影响。结果显示，受访者能够应对环境不确定性并维持安全行为。