技术威胁规避理论(TTAT)与网络钓鱼的安全意识--个人威胁分析

Indah Daila Sari, Dedy Hariyadi, R. Sahtyawan, Netania Indi Kusumaningtyas
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摘要

网络钓鱼是一种网络犯罪,涉及通过使用电子邮件、短信或受损网站获取敏感信息。网络钓鱼的影响是由技术威胁规避理论中的因素造成的。阻止网络钓鱼攻击的唯一最佳方法就是提高用户或最终用户对发生网络钓鱼攻击风险的认识(人类防火墙)。为确定提高用户知识的下一步措施,有必要衡量网络安全意识,尤其是针对网络钓鱼攻击的意识。确定日惹 Jenderal Achmad Yani FTTI 大学学生的几个重要网络安全意识。本案例的调查包括网络钓鱼测试,还采用了在线观察法,观察者根据技术威胁规避理论(TTAT)提出问题。利用 MANOVA 分析方法,对影响网络安全意识的因素进行了分析。根据对网络钓鱼测试以及样本人群在线问卷的分析和检测,结果显示样本人群的网络安全意识水平较低。而利用 MANOVA 分析方法对网络安全影响因素进行分析,结果显示 sig.>0.05 值,因此拒绝 h0。根据研究结果,可以得出结论:快三学院学生仍然容易受到网络钓鱼攻击。利用 MANOVA 方法进行的因子分析显示,因果因子会影响受访者的网络安全意识水平,但因果因子之间没有显著差异。
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Analisis Tingkat Security Awareness-Personal Threat Terhadap Ancaman Phishing Dengan Metode Technology Threat Avoidance Theory (TTAT)
Phishing is a sort of cybercrime that involves obtaining sensitive information through the use of email, SMS, or compromised websites. The effects of phishing are caused by factors in the Technology Threat Avoidance Theory. The single best way to stop phishing attacks is to increase awareness of the risk of them happening among users or end users (human firewall). To determine the next steps in raising user knowledge, it is necessary to measure cybersecurity awareness, particularly against phishing assaults. Identify a few significant cybersecurity awareness of FTTI University of Jenderal Achmad Yani students in Yogyakarta. The investigation in this case included a phishing test and also employed online observation using observers who were asked questions based on the Technology Threat Avoidance Theory (TTAT). Using the MANOVA analysis method, factors influencing cybersecurity awareness analysis is conducted. Based on the analysis and testing of phishing tests as well as online questionnaires from the sample population, it shows that the sample is at a poor level of awareness. While the analysis of cybersecurity influence factors using the MANOVA analysis method shows that the results of the sig.> 0.05 value so that h0 is rejected. Based on the results of the study, it was concluded that FTTI students were still vulnerable to phishing attacks. Factor analysis using the MANOVA method shows that the dependent factor affects the level of cybersecurity awareness of the respondents but there is no significant difference between the dependent factors.
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