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自动化信任倾向、系统可靠性和反馈对用户网络钓鱼检测的影响。

The effect of automation trust tendency, system reliability and feedback on users' phishing detection.

作者信息

Zhou Ying, Cui Xinyue, Qu Weina, Ge Yan

机构信息

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.

出版信息

Appl Ergon. 2022 Jul;102:103754. doi: 10.1016/j.apergo.2022.103754. Epub 2022 Mar 24.

Abstract

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.

摘要

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。

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