NeTS: Small: Collaborative Research: Leveraging Personalized Internet Services to Combat Online Trolling

今天，用户进行的几乎每一次浏览点击都是由与各种在线服务(例如，广告网络、在线社交网络、电子商务平台)相关联的众多跟踪器收集的。用户经常对缺乏隐私和对其个人数据的控制表示担忧。尽管如此，尽管做出了大量努力来揭露和控制这种普遍存在的行为，但现实情况是，用户不断接受更新的在线隐私政策，这反过来又允许收集更多的个人数据。这个项目探索了为了用户本身和网络服务的利益而重新使用这个广泛的跟踪基础设施，目标是防止在线恶意攻击(各种团体通过留下有偏见的、虚假的、误导性的和不真实的评论来影响互联网上的舆论，然后人为地放大他们的评级)。该项目旨在展示如何将跟踪基础设施重新用作用户的“指纹”，从而为第三方网站提供一种轻量级且保护隐私的身份识别形式。智力优势：更详细地说，该项目探索是否有可能利用无处不在的用户在线跟踪来直接造福于用户本身。尽管在过去十年中，几乎每一次浏览器点击都受到无数在线追踪器的监控，但用户在使用互联网时往往很难证明自己的身份和独特性。另一方面，许多依赖开放成员资格的系统经常成为在线恶意攻击的目标，通常是通过多身份(Sybil)攻击。在今天的互联网上，有组织的巨魔已经成为一个严重的问题；一些人认为它可以对社会产生深远的影响。该项目正在开发一种系统，该系统将直接利用在线追踪器所做的工作来记录和解释用户的行为。关键的想法是使用随时可用的个性化内容-由在线追踪器实时生成--作为一种手段，以无缝和隐私保护的方式验证在线用户的独特性。将由用户收集、去除识别内容并上传的这种个性化内容将被用来构建用户的多跟踪器向量表示。然后，向量表示将充当每个用户的唯一“指纹”，使攻击者很难表现出他们是许多不同的用户，从而减少许多恶意攻击。Broader影响：该项目有能力通过授权互联网社区来打击在线恶意攻击，从而产生重大影响。正在开发的系统不仅将帮助许多在线社区重新获得无巨魔的环境，而且还将重新利用现有的广泛跟踪基础设施，为最终用户和网站提供切实的好处。私营部门计划设计和传播基于个性化的反欺诈系统作为开源软件，这将使有效的欺诈检测和反欺诈方法和系统成为可能。教育是该项目不可或缺的一部分，私人投资机构计划利用现有的机构和特殊计划，从代表性不足的群体中招募学生加入该项目。

Today, almost every browsing click that users make is collected by numerous trackers associated with a variety of online services (e.g., advertising networks, online social networks, e-commerce platforms). Users have often expressed concern about the lack of privacy and control over their personal data. Nonetheless, despite a substantial effort to expose and control this prevalent behavior, the reality is that users keep accepting updated online privacy policies, which in turn grant the gathering of more personal data. This project explores re-using this extensive tracking infrastructure for the benefits of both the users themselves and web services, with a goal of preventing online trolling (scenarios in which various groups deploy tactics to influence public opinion on the Internet, by leaving biased, false, misleading, and inauthentic comments, and then artificially amplifying their ratings). The project aims to show how the tracking infrastructure can be re-used as a user "fingerprint", allowing a lightweight and privacy-preserving form of identification for third-party web sites. Intellectual Merit: In more detail, the project explores whether it is possible to utilize the ubiquitous online tracking of users for the direct benefit of the users themselves. Despite the fact that almost every browser click made over the last decade has been monitored by numerous online trackers, users often have a hard time proving their identity and uniqueness while using the Internet. On the other hand, many systems that rely upon open membership are often targets of online trolling, often via multiple-identity (Sybil) attacks. Organized trolling has become a serious problem in today's Internet; some argue that it can have a profound impact on the society. The project is developing a system that would take direct advantage of the work online trackers do to record and interpret users' behavior. The key idea is to use the readily-available personalized content---generated by online trackers in real-time---as a means to verify an online user's uniqueness in a seamless and privacy-preserving manner. This personalized content, which would be collected by the users, stripped of identifying content, and uploaded, would be used to construct a multi-tracker vector representation of the user. The vector representation would then serve as a unique "fingerprint" of each user, making it difficult for attackers to appear as if they were many distinct users, thereby mitigating many trolling attacks.Broader Impacts: The project has the capacity to make a significant impact by empowering the Internet community to combat the online trolling problem. The system under development will not only help numerous online communities regain trolling-free environments, but also re-use the extensive tracking infrastructure that already exists to provide tangible benefits for both end users and web sites. The PIs plan to design and disseminate personalization-based counter-trolling system as open-source software, which will enable effective trolling detection and counter-trolling methods and systems. Education is an integral part of the project, and the PIs plan to leverage existing institutional and special programs to recruit students from underrepresented groups into the project.