EAGER: Behavior-Based Incentive Mechanism Design for Crowd Defense against Phishing Attacks

这项研究旨在防止网络钓鱼攻击带来的危害。钓鱼攻击在过去几年里一直在上升，仅在2013年就有近45万次攻击和创纪录的估计损失超过59亿美元。这些攻击试图通过欺诈性电子邮件获取个人信息，如用户名和密码。钓鱼邮件正变得越来越有针对性，使用目标受害者的个人信息，试图看起来像是真实的电子邮件，并提高对攻击的响应率。如果收到钓鱼邮件的大量参与者能够使用虚假或欺骗性信息对其进行战略性回应，攻击者将被大量回复淹没和误导，从而增加定位受害者的成本。这样，容易成为钓鱼诈骗受害者的易受攻击的用户将隐藏在多个虚假回复中。防御者的大群体合作行为会显著增加攻击成本，从而降低攻击者发送钓鱼邮件的经济诱因。这种类型的防御机制被称为群体防御。本项目将从心理、经济、行为、技术等方面对人群防御机制设计进行全方位的探讨。冠层防御是扭转攻防双方不对称优势的关键防御机制。这项研究旨在了解群防者行为中的心理和经济因素，创建必要的行为博弈论设计框架，并开发一个概念验证自动化软件系统，使用户能够协调和自动响应网络钓鱼。为反网络钓鱼人群防御开发的分析和设计方法可以广泛应用于其他安全问题，如分布式拒绝服务攻击(DDoS)、高级持续威胁(APT)和协调侦察。在这个项目中创建的工具将作为开放源码发布，以建立一个更具协作性和可信度的网络空间。私人投资机构致力于通过外联活动进行公共教育，这将进一步增加妇女和少数群体作为研究生和本科生参与该项目。

This research is aimed at preventing harm from phishing attacks. Phishing attacks have been on the rise in the last few years with nearly 450,000 attacks and record estimated losses of over USD $5.9 billion just in the year 2013 alone. These attacks attempt to acquire personal information, such as username and passwords, through fraudulent emails. Phishing emails are becoming more targeted, using personal information about their intended victims, in an attempt to seem like authentic emails and improve the response rate to the attacks. If a large number of participants who receive a phishing email can respond to it strategically using fake or deceptive information, the attacker will be overwhelmed and misled by the number of responses, and thus making it more costly to locate the victim. In this way, vulnerable users who tend to fall victim to phishing scams will be hidden in a number of fake responses. The cooperative large-population behavior of the defenders can increase significantly the cost of attack, and hence reduce the economic incentives for the attacker to send phishing email. This type of defense mechanism is called crowd defense. This project will holistically explore the psychological, economic, behavioral, and technical aspects of crowd defense mechanism design.Crowd defense is a critical defense mechanism to reverse the asymmetric advantage from the attacker to the defender. The research aims to understand the psychological and economic factors in the behavior of crowd defenders, create essential behavioral game-theoretic design frameworks, and develop a proof-of-concept automated software system that enables users to coordinate and respond automatically to phishing. The analytical and design methodologies developed for anti-phishing crowd defense can be broadly applied to other security problems, such as distributed denial of service attacks (DDoS), advanced persistent threats (APT), and coordinated reconnaissance. The tools created in this project will be released as open-source for building a more collaborative and trustworthy cyberspace. The PIs are committed to public education through outreach activities that will further increase the participation of women and minorities as graduate and undergraduate students in the project.