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Case Study: Disclosure of Indirect Device Fingerprinting in Privacy Policies

机译:案例研究:披露隐私政策中的间接装置指纹识别

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Recent developments in online tracking make it harder for individuals to detect and block trackers. This is especially true for device fingerprinting techniques that websites use to identify and track individual devices. Direct trackers - those that directly ask the device for identifying information - can often be blocked with browser configurations or other simple techniques. However, some sites have shifted to indirect tracking methods, which attempt to uniquely identify a device by asking the browser to perform a seemingly-unrelated task. One type of indirect tracking known as Canvas fingerprinting causes the browser to render a graphic recording rendering statistics as a unique identifier. Even experts find it challenging to discern some indirect fingerprinting methods. In this work, we aim to observe how indirect device fingerprinting methods are disclosed in privacy policies, and consider whether the disclosures are sufficient to enable website visitors to block the tracking methods. We compare these disclosures to the disclosure of direct fingerprinting methods on the same websites. Our case study analyzes one indirect fingerprinting technique, Canvas fingerprinting. We use an existing automated detector of this fingerprinting technique to conservatively detect its use on Alexa Top 500 websites that cater to United States consumers, and we examine the privacy policies of the resulting 28 websites. Disclosures of indirect fingerprinting vary in specificity. None described the specific methods with enough granularity to know the website used Canvas fingerprinting. Conversely, many sites did provide enough detail about usage of direct fingerprinting methods to allow a website visitor to reliably detect and block those techniques. We conclude that indirect fingerprinting methods are often technically difficult to detect, and are not identified with specificity in legal privacy notices. This makes indirect fingerprinting more difficult to block, and therefore risks disturbing the tentative armistice between individuals and websites currently in place for direct fingerprinting. This paper illustrates differences in fingerprinting approaches, and explains why technologists, technology lawyers, and policymakers need to appreciate the challenges of indirect fingerprinting.
机译:在线跟踪中的最新进展使个人更难以检测和阻止跟踪器。对于网站用于识别和跟踪各个设备的设备指纹技术尤其如此。直接跟踪器 - 直接询问设备识别信息的追踪器通常可以通过浏览器配置或其他简单的技术阻止。但是,某些网站已转移到间接跟踪方法,该方法尝试通过询问浏览器执行看似不相关的任务来唯一地识别设备。称为CANVAS指纹识别的一种间接跟踪导致浏览器将图形记录渲染统计数据呈现为唯一标识符。甚至专家们发现它挑战了一些间接指纹方法。在这项工作中,我们的目标是观察隐私政策中公开了间接设备指纹方法的方法,并考虑披露是否足以使网站访问者能够阻止跟踪方法。我们将这些披露与在同一网站上的直接指纹识别方法的披露进行比较。我们的案例研究分析了一种间接指纹技术,帆布指纹识别。我们使用本指纹识别技术的现有自动检测器保守地检测其在亚历克萨前500个网站上的使用,以迎合美国消费者,我们检查由此产生的28个网站的隐私政策。间接指纹识别的披露在特异性方面变化。没有描述具有足够粒度的特定方法,以了解该网站使用的帆布指纹识别。相反,许多网站确实为使用直接指纹方法的使用提供了足够的细节,以允许网站访问者可靠地检测和阻止这些技术。我们得出结论,间接指纹方法经常在技术上难以检测,并且没有以法律隐私声明的特异性确定。这使得间接指纹识别更难以阻挡,因此风险扰乱目前用于直接指纹识别的个人和网站之间的暂定停电器。本文说明了指纹识别方法的差异,并解释了为什么技术人员,技术律师和政策制定者需要欣赏间接指纹识别的挑战。

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