测量在恶意内容中受害的可能性

M. Hale, R. Gamble, John Hale, Charles Haney, Jessica Lin, Charles Walter
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引用次数: 5

摘要

向用户发送恶意内容以获取人员、财务或知识产权已经成为一个价值数十亿美元的犯罪企业。这些内容主要以电子邮件、社交媒体帖子和网络钓鱼网站的形式呈现。用户培训计划旨在通过提高警惕性来尽量减少恶意内容的影响。针对特定用户缺陷的培训效果最好。然而,定制培训需要了解恶意内容是如何伤害用户的。在本文中,我们以降级和复杂的形式将一组恶意内容设计因素与它们形成受害预测指标的潜力联系起来。这些设计因素是对来自电子邮件、社交媒体和网站的100多篇内容进行分析后得出的。我们使用内容样本和基于游戏的模拟平台进行了一项实验,以评估受害预测指标的有效性。实验结果及其分析是评价的一部分。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Measuring the Potential for Victimization in Malicious Content
Sending malicious content to users for obtaining personnel, financial, or intellectual property has become a multi-billion dollar criminal enterprise. This content is primarily presented in the form of emails, social media posts, and phishing websites. User training initiatives seek to minimize the impact of malicious content through improved vigilance. Training works best when tailored to specific user deficiencies. However, tailoring training requires understanding how malicious content victimizes users. In this paper, we link a set of malicious content design factors, in the form of degradations and sophistications, to their potential to form a victimization prediction metric. The design factors examined are developed from an analysis of over 100 pieces of content from email, social media and websites. We conducted an experiment using a sample of the content and a game-based simulation platform to evaluate the efficacy of our victimization prediction metric. The experimental results and their analysis are presented as part of the evaluation.
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