Zhou Ying, Cui Xinyue, Qu Weina, Ge Yan
CAS Key Laboratory of Behavioral Science, Institute of Psychology, Chinese Academy of Sciences, Beijing, China; Department of Psychology, University of Chinese Academy of Sciences, Beijing, China.
CAS Key Laboratory of Behavioral Science, Institute of Psychology, Chinese Academy of Sciences, Beijing, China; Department of Psychology, University of Chinese Academy of Sciences, Beijing, China.
Appl Ergon. 2022 Jul;102:103754. doi: 10.1016/j.apergo.2022.103754. Epub 2022 Mar 24.
As a new intrusion method in the security field, phishing poses an enormous threat to network security and personal privacy. Thus, improving the level of network security and preventing phishing are a matter of great concern to both the state and researchers. A 2 (automation trust tendency) *2 (system reliability level) *2 (feedback) between-subjects design was adopted to study the impact of individual characteristics and system features on phishing detection. Three hundred ninety-eight participants completed a phishing email task to identify whether 40 emails were legitimate or fraudulent. The results showed that systems with feedback and high reliability improve users' performance in email identification. Users with a high tendency towards automation trust have a higher risk of phishing. However, feedback from the system helps calibrate a high automation trust tendency. These research results can promote an understanding of phishing prevention mechanisms and provide support for the design of email defence systems.
作为安全领域的一种新型入侵方式,网络钓鱼对网络安全和个人隐私构成了巨大威胁。因此,提高网络安全水平、防范网络钓鱼是国家和研究人员都极为关注的问题。本研究采用2(自动化信任倾向)×2(系统可靠性水平)×2(反馈)的被试间设计,来探究个体特征和系统特征对网络钓鱼检测的影响。398名参与者完成了一项网络钓鱼邮件任务,以判断40封邮件是合法还是欺诈性的。结果表明,具有反馈且可靠性高的系统能提高用户在邮件识别方面的表现。自动化信任倾向高的用户遭受网络钓鱼的风险更高。然而,系统反馈有助于校准较高的自动化信任倾向。这些研究结果有助于增进对网络钓鱼防范机制的理解,并为电子邮件防御系统的设计提供支持。