CRII: SaTC: A Framework to Defend Against Sockpuppet Connection Requests in Social Networks

该奖项全部或部分由《2021年美国救援计划法案》（公法117-2）资助。攻击者利用在线社交网络（OSNs）中人与人之间的链接访问私人和敏感用户数据，在受害者的时间轴和新闻源上发布虚假或滥用信息，以及欺骗和影响受害者的看法。社交媒体使用的大规模增长激励了犯罪者通过虚假的“马甲”账户连接用户，由于缺乏对所声明信息的充分验证，这种攻击通常会成功。该项目的目标是显著扩展对在线社交网络中身份欺骗和滥用的理解，并设计和构建干预机制来减轻这些类型的攻击。该项目团队将与社交媒体用户合作，创建一个数字框架，以评估用户成为马甲攻击受害者的风险，教育他们了解这些攻击，并帮助他们仔细检查连接邀请，避免接受来自可疑账户的邀请。我们的目标是开发新一代的防马偶解决方案，有可能帮助保护数百万脆弱的OSN用户免受性侵犯者、在线欺诈者、骗子、对手或恶意黑客的攻击。该项目将建立一个基于认知心理学、用户体验研究和机器学习方法的数字框架，以防御在线社交网络中的sockpuppet连接请求。在第一个研究重点中，研究人员将开发调查工具和用户研究，以调查osn中悬而未决的连接决策、动机和行为。本研究的结果将用于开发下一个研究，研究人员将通过未决连接决策分类器实现“垃圾邮件连接”文件夹。最后，研究人员将开发一种新的在线社交网络待处理连接处理接口。这将被设计为现有社交网络之上的一层，可用于管理和评估真实社交网络背景下围绕袜子玩偶的教育和界面干预，同时允许研究团队解决处理袜子玩偶连接和人们私人数据的道德和法律考虑。总之，这项工作将增强对与社会网络风险相关的即时动机和行为的理解，并帮助社会学家从社会网络提供的未被探索的社会和空间维度中获得更深入的见解，以检验相关理论。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

This award is funded in whole or in part under the American Rescue Plan Act of 2021 (Public Law 117-2).Links between people in Online Social Networks (OSNs) have been used by attackers to access private and sensitive user data, post false or abusive information on the timelines and news feeds of victims, and scam and influence the perceptions of victims. The massive growth of social media usage has incentivized perpetrators to connect users through fake "sockpuppet" accounts, an attack that is often successful due to the lack of adequate verification of declared information. The goal of this project is to significantly expand the understanding of identity deception and abuse in online social networks, and design and build intervention mechanisms to mitigate these types of attacks. The project team will work with social media users to create a digital framework that can assess users' risk of falling victim to sockpuppet attacks, educate them about these attacks, and help them carefully examine connection invites and avoid accepting invitations from suspicious accounts. This goal is to develop a new generation of sockpuppet prevention solutions that have the potential to help protect millions of vulnerable OSN users from sexual predators, online fraudsters, scammers, adversaries, or malicious hackers.This project will build a digital framework rooted in cognitive psychology, UX research, and machine learning methods to defend against sockpuppet connection requests in online social networks. In a first research thrust, the researchers will develop survey instruments and user studies to investigate pending connection decisions, motivations, and behaviors in OSNs. The findings from this research thrust will be utilized to develop the next thrust, where the researchers will implement a "spam connection" folder through a pending connection decision classifier. Finally, the researchers will ievelop a novel Online Social Network Pending Connection Processing Interface .This will be designed as a layer on top of existing social networks that can be used to administer and assess educational and interface interventions around sockpuppets in the context of real social networks, while allowing the research team to address ethical and legal considerations of working with sockpuppet connections and people's private data. Together, this work will both enhance the understanding of just-in-time motivations and behaviors related to social network risks and help sociologists gain deeper insights from underexplored social and spatial dimensions provided by social networks to test relevant theories.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.