Canfield Casey Inez, Fischhoff Baruch, Davis Alex
Carnegie Mellon University, Pittsburgh, Pennsylvania
Carnegie Mellon University, Pittsburgh, Pennsylvania.
Hum Factors. 2016 Dec;58(8):1158-1172. doi: 10.1177/0018720816665025. Epub 2016 Aug 25.
We use signal detection theory to measure vulnerability to phishing attacks, including variation in performance across task conditions.
Phishing attacks are difficult to prevent with technology alone, as long as technology is operated by people. Those responsible for managing security risks must understand user decision making in order to create and evaluate potential solutions.
Using a scenario-based online task, we performed two experiments comparing performance on two tasks: detection, deciding whether an e-mail is phishing, and behavior, deciding what to do with an e-mail. In Experiment 1, we manipulated the order of the tasks and notification of the phishing base rate. In Experiment 2, we varied which task participants performed.
In both experiments, despite exhibiting cautious behavior, participants' limited detection ability left them vulnerable to phishing attacks. Greater sensitivity was positively correlated with confidence. Greater willingness to treat e-mails as legitimate was negatively correlated with perceived consequences from their actions and positively correlated with confidence. These patterns were robust across experimental conditions.
Phishing-related decisions are sensitive to individuals' detection ability, response bias, confidence, and perception of consequences. Performance differs when people evaluate messages or respond to them but not when their task varies in other ways.
Based on these results, potential interventions include providing users with feedback on their abilities and information about the consequences of phishing, perhaps targeting those with the worst performance. Signal detection methods offer system operators quantitative assessments of the impacts of interventions and their residual vulnerability.
我们运用信号检测理论来衡量对网络钓鱼攻击的易感性,包括不同任务条件下的表现差异。
只要技术由人来操作,仅靠技术很难防范网络钓鱼攻击。负责管理安全风险的人员必须了解用户的决策过程,以便创建和评估潜在的解决方案。
通过一个基于场景的在线任务,我们进行了两项实验,比较了两项任务的表现:检测,即判断一封电子邮件是否为网络钓鱼邮件;以及行为,即决定如何处理一封电子邮件。在实验1中,我们操纵了任务顺序和网络钓鱼基础比率的通知。在实验2中,我们改变了参与者执行的任务。
在两项实验中,尽管参与者表现出谨慎行为,但他们有限的检测能力使他们容易受到网络钓鱼攻击。更高的敏感性与信心呈正相关。将电子邮件视为合法邮件的意愿更强与对自身行为后果的感知呈负相关,与信心呈正相关。这些模式在不同实验条件下都很稳健。
与网络钓鱼相关的决策对个人的检测能力、反应偏差、信心以及对后果的感知很敏感。当人们评估邮件或对其做出反应时表现会有所不同,但当任务以其他方式变化时则不然。
基于这些结果,潜在的干预措施包括向用户提供关于其能力的反馈以及网络钓鱼后果的信息,或许针对表现最差的用户。信号检测方法为系统操作员提供了对干预措施影响及其剩余易感性的定量评估。