Yanis Boussad, Yuanxuan Yang, Andrew Tomlinson, Susan Grant-Muller
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引用次数: 0
Abstract
Bluetooth Low Energy (BLE) is a widely used wireless technology which offers a wide range of applications. However, the introduction of MAC address randomization to preserve the users’ privacy makes it more challenging to leverage all its potential. In this paper, we present McMatcher, a privacy-preserving, novel methodology for matching random MAC addresses from BLE devices. McMatcher uses a symbolic representation of the RSSI time series to build characterizing vectors, embedding both the temporal as well as the signal strength (RSSI) properties of the BLE signal. Our methodology achieves 100% accuracy in matching 92 MAC addresses from 16 smartphones, in a dataset containing 332 MAC addresses in total. As opposed to previous works, our methodology does not require any model training, and relies only on the RSSI measurements. The computational simplicity of McMatcher allows matching MAC addresses in realtime, taking only 230ms for a set of 18 MAC addresses.
蓝牙低功耗(BLE)是一种广泛应用的无线技术,具有广泛的应用领域。然而,为保护用户隐私而引入的 MAC 地址随机化技术使其更难发挥全部潜力。在本文中,我们介绍了 McMatcher,这是一种保护隐私的新方法,用于匹配 BLE 设备的随机 MAC 地址。McMatcher 使用 RSSI 时间序列的符号表示来构建特征向量,同时嵌入 BLE 信号的时间和信号强度(RSSI)属性。在总共包含 332 个 MAC 地址的数据集中,我们的方法对来自 16 部智能手机的 92 个 MAC 地址的匹配准确率达到了 100%。与之前的研究不同,我们的方法不需要任何模型训练,只依赖于 RSSI 测量值。麦克马彻的计算简单,可以实时匹配 MAC 地址,一组 18 个 MAC 地址的匹配仅需 230 毫秒。