论文标题

用户确实对smishing做出了回应

Users really do respond to smishing

论文作者

Rahman, Muhammad Lutfor, Timko, Daniel, Wali, Hamid, Neupane, Ajaya

论文摘要

文本网络钓鱼消息(称为Smishing)是一种社会工程攻击,在其中创建了假短信,并用来吸引用户响应这些消息。这些消息旨在获取用户凭据,在手机上安装恶意软件或启动Smishing攻击。他们要求用户回复他们的消息,单击将其重定向到网络钓鱼网站的URL或调用提供的号码。每天都有smishing攻击的影响,成千上万的移动用户受到影响。通过Tu等人的作品汲取灵感。 (USENIX Security,2019年)关于Robocalls和Tischer等人。 (IEEE安全与隐私研讨会,2016年)在USB驱动器上,本文调查了Smishing的原因。因此,我们设计了Smishing实验,并向265位用户发送网络钓鱼SMS,以衡量打击攻击的功效。我们向参与者发送了八条假短信,并在测试后的调查中记录了他们的点击,回复和致电答复以及他们的反馈。我们的结果表明,我们有16.92%的参与者可能因我们的打isth攻击而陷入困境。为了测试重复的网络钓鱼,我们对一组随机选择的参与者进行了第二轮击打攻击,其消息与他们在第一轮中收到的消息不同。结果,我们观察到12.82%的袭击可能再次下降。使用逻辑回归,我们观察到用户回复和点击操作的组合增加了用户与单击相比,用户会响应我们的Smishing消息的几率。此外,当将Facebook和Walmart实体方案与IRS基线进行比较时,我们发现了类似的统计学显着增加。

Text phish messages, referred to as Smishing is a type of social engineering attack where fake text messages are created, and used to lure users into responding to those messages. These messages aim to obtain user credentials, install malware on the phones, or launch smishing attacks. They ask users to reply to their message, click on a URL that redirects them to a phishing website, or call the provided number. Thousands of mobile users are affected by smishing attacks daily. Drawing inspiration by the works of Tu et al. (USENIX Security, 2019) on Robocalls and Tischer et al. (IEEE Symposium on Security and Privacy, 2016) on USB drives, this paper investigates why smishing works. Accordingly, we designed smishing experiments and sent phishing SMSes to 265 users to measure the efficacy of smishing attacks. We sent eight fake text messages to participants and recorded their CLICK, REPLY, and CALL responses along with their feedback in a post-test survey. Our results reveal that 16.92% of our participants had potentially fallen for our smishing attack. To test repeat phishing, we subjected a set of randomly selected participants to a second round of smishing attacks with a different message than the one they received in the first round. As a result, we observed that 12.82% potentially fell for the attack again. Using logistic regression, we observed that a combination of user REPLY and CLICK actions increased the odds that a user would respond to our smishing message when compared to CLICK. Additionally, we found a similar statistically significant increase when comparing Facebook and Walmart entity scenario to our IRS baseline.

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