使用Wi-Fi数据包的MAC地址随机化容忍人群监控系统

Yuyi Cai, Manabu Tsukada, H. Ochiai, H. Esaki
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引用次数: 2

摘要

Wi-Fi包中的媒体访问控制(MAC)地址可用于有益的活动,如拥挤度估计、营销和危险图。然而,2014年左右引入的MAC地址随机化系统使所有传统的基于MAC地址的人群监控系统对同一设备进行多次计数。因此,需要创建一种新的容忍MAC地址随机化的人群监控系统,以准确估计设备数量。本文提出了Vision和TrueSight两种新的人群监控算法来估计设备数量,以证明基于mac地址的人群监控仍然是可能的。除了探测请求外,Vision还使用数据包和信标数据包来减轻随机化的影响。此外,TrueSight还使用序列号和分层聚类来估计设备的数量。本研究的实验结果表明,即使在不安装任何特殊软件的情况下,Vision也可以将随机生成的440个MAC地址集合为一组,只计数一次,TrueSight可以估计出设备的数量,准确率超过75%,可接受的误差范围为1。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
MAC address randomization tolerant crowd monitoring system using Wi-Fi packets
Media access control (MAC) addresses inside Wi-Fi packets can be used for beneficial activities such as crowdedness estimation, marketing, and hazard maps. However, the MAC address randomization systems introduced around 2014 make all conventional MAC-address-based crowd monitoring systems count the same device more than once. Therefore, there is a need to create a new crowd monitoring system tolerant to MAC address randomization to estimate the number of devices accurately. In this paper, Vision and TrueSight, two new crowd monitoring algorithms that estimate the number of devices, are proposed to prove that MAC-address-based crowd monitoring is still possible. In addition to probe requests, Vision uses data packets and beacon packets to mitigate the influence of randomization. Moreover, TrueSight uses sequence numbers and hierarchical clustering to estimate the number of devices. The experimental results of this study show that even without installing any special software, Vision can gather 440 randomly generated MAC addresses into one group and count only once, and TrueSight can estimate the number of devices with an accuracy of more than 75% with an acceptable error range of 1.
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