On the feasibility of profiling internet users based on volume and time of usage

S. Sarmadi, Mingyang Li, S. Chellappan
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引用次数: 4

Abstract

In this paper, we address the issue of profiling users over the Internet using meta-data logs derived from network flow data (hence preserving a high degree of privacy). In this broader context, we specifically aim to empirically demonstrate that Internet volume and time of usage of humans do exhibit repeatable behavior over time. In our experimental study, Internet usage statistics of octets and duration (collected via privacy-preserving NetFlow records) of 66 student subjects in a college campus was recorded for a month. Subsequently, using state-of-the-art statistical techniques, we demonstrate how the Internet usage of any particular subject is highly-correlated with usage of the same subject over multiple time scales, while simultaneously being distinct from usage of other subjects. We derive interesting and practically useful trends on the relationship between the degree of distinguishability and the window time chosen to do the profiling. We also present discussions on the practical applications of this new study.
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基于使用量和使用时间对互联网用户进行分析的可行性研究
在本文中,我们使用源自网络流数据的元数据日志解决了在互联网上分析用户的问题(因此保留了高度的隐私)。在这个更广泛的背景下,我们的具体目标是通过经验证明,随着时间的推移,人类使用互联网的数量和时间确实表现出可重复的行为。在我们的实验研究中,我们记录了大学校园中66名学生一个月的网络使用统计数据(通过保护隐私的NetFlow记录收集)。随后,使用最先进的统计技术,我们展示了任何特定主题的互联网使用如何与多个时间尺度上同一主题的使用高度相关,同时与其他主题的使用截然不同。我们在可分辨度和选择进行分析的窗口时间之间的关系上得出了有趣和实用的趋势。我们还对这项新研究的实际应用进行了讨论。
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