从指纹到足迹:通过网络空间Cookie日志揭示物理世界隐私泄露

Huandong Wang, Chen Gao, Yong Li, Zhi-Li Zhang, Depeng Jin
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引用次数: 16

摘要

众所周知,在线服务通过用户的在线服务标识符(id)使用各种cookie来跟踪用户,换句话说,当用户访问在线服务时,在网络空间中留下了各种“指纹”。当用户在现实世界中漫游,同时通过移动设备访问在线服务时,他们也会在现实世界中留下一系列“足迹”,即关于他们实际位置的提示。这对用户隐私构成了一个潜在的新威胁:人们可以将用户在网络空间中留下的“指纹”与在物理世界中留下的“足迹”联系起来,推断和揭示用户物理世界隐私的泄露,例如用户在物理世界中的频繁位置或移动轨迹——我们将这个问题称为通过用户网络空间隐私泄露来泄露用户物理世界隐私。在本文中,我们解决了以下基本问题:如果我们能够在没有任何物理位置信息的情况下获得如此多样化的网络数据集,那么什么样的用户物理世界隐私可能会泄露,以及泄露多少用户物理世界隐私。为了对这些问题进行深入调查,我们利用DPI系统在中国上海最大的互联网运营商之一的路由器上收集的网络数据,持续一个月。我们将基本问题分解为三个问题:i)通过移动模式挖掘将属于同一个人的各种在线用户id链接起来;Ii)根据用户随时间的移动模式进行物理位置分类;iii)跟踪用户的身体移动。通过开发解决这些问题的新颖有效的方法,我们证明了通过用户网络空间隐私泄露导致用户物理世界隐私泄露的问题不是假设的,而是对用户隐私构成了真正的潜在威胁。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
From Fingerprint to Footprint: Revealing Physical World Privacy Leakage by Cyberspace Cookie Logs
It is well-known that online services resort to various cookies to track users through users' online service identifiers (IDs) - in other words, when users access online services, various "fingerprints" are left behind in the cyberspace. As they roam around in the physical world while accessing online services via mobile devices, users also leave a series of "footprints" -- i.e., hints about their physical locations - in the physical world. This poses a potent new threat to user privacy: one can potentially correlate the "fingerprints" left by the users in the cyberspace with "footprints" left in the physical world to infer and reveal leakage of user physical world privacy, such as frequent user locations or mobility trajectories in the physical world - we refer to this problem as user physical world privacy leakage via user cyberspace privacy leakage. In this paper we address the following fundamental question: what kind - and how much - of user physical world privacy might be leaked if we could get hold of such diverse network datasets even without any physical location information. In order to conduct an in-depth investigation of these questions, we utilize the network data collected via a DPI system at the routers within one of the largest Internet operator in Shanghai, China over a duration of one month. We decompose the fundamental question into the three problems: i) linkage of various online user IDs belonging to the same person via mobility pattern mining; ii) physical location classification via aggregate user mobility patterns over time; and iii) tracking user physical mobility. By developing novel and effective methods for solving each of these problems, we demonstrate that the question of user physical world privacy leakage via user cyberspace privacy leakage is not hypothetical, but indeed poses a real potent threat to user privacy.
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