论文标题
集体混淆和众包
Collective Obfuscation and Crowdsourcing
论文作者
论文摘要
众包技术依靠人群输入可能对决策至关重要的信息。这项工作研究了在报告技术的背景下混淆。我们表明，报告平台的广泛使用具有独特的安全性和隐私影响，并引入了威胁模型和相应的分类法，以概述该领域中许多攻击向量中的一些。然后，我们对有争议的现实世界报告热线的呼叫日志数据集进行了经验分析，并确定旨在阻碍平台合法性的协调混淆策略。我们提出了各种统计措施，以量化这种混淆策略在我们数据集中报告攻击的结构和语义特征方面的强度。
Crowdsourcing technologies rely on groups of people to input information that may be critical for decision-making. This work examines obfuscation in the context of reporting technologies. We show that widespread use of reporting platforms comes with unique security and privacy implications, and introduce a threat model and corresponding taxonomy to outline some of the many attack vectors in this space. We then perform an empirical analysis of a dataset of call logs from a controversial, real-world reporting hotline and identify coordinated obfuscation strategies that are intended to hinder the platform's legitimacy. We propose a variety of statistical measures to quantify the strength of this obfuscation strategy with respect to the structural and semantic characteristics of the reporting attacks in our dataset.
