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Revisiting Urban War Nibbling: Mobile Passive Discovery of Classic Bluetooth Devices Using Ubertooth One

机译:重新审视城市战争:使用Ubertooth One被动移动发现经典蓝牙设备

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The ubiquitous nature of Bluetooth technology presents opportunities for intelligence gathering based on historical and real-time device presence data. This information can be of value to law enforcement agencies, intelligence organizations, and industry. Despite the introduction of the Bluetooth Low Energy standard that incorporates anonymity preservation mechanisms, the presence of devices that support Classic Bluetooth that uses unique and persistent device identifiers is expected to remain significant for a number of years. The common approach to finding discoverable Classic Bluetooth devices relies on a standard inquiry process that is not truly passive. Furthermore, this approach fails to detect devices that remain undiscoverable. Ubertooth One, a low-cost open source Bluetooth development platform, can assist with overcoming this limitation in a truly passive manner, making it an attractive digital forensic instrument. Using vehicle-based sensors and parallel multi-method device discovery, we conduct a practical evaluation of Ubertooth One for passive discovery and contrast its discovery rate to the standard method. Based on 83 comparative field experiments, we show that Ubertooth One can produce forensically sound observations while able to discover up to ten times as many devices. We also show that this method can identify repeat device presence, as we observe 2370 instances of repeat observations on different days in single and multiple location scenarios. We conclude that this passive technique can complement the standard method and has the potential be used as a viable alternative.
机译:蓝牙技术无处不在,为基于历史和实时设备状态数据的情报收集提供了机会。此信息可能对执法机构,情报机构和行业有价值。尽管引入了结合了匿名性保留机制的低功耗蓝牙标准,但支持使用独特且持久的设备标识符的经典蓝牙的设备的存在预计仍将持续数年。查找可发现的经典蓝牙设备的常用方法依赖于标准的查询过程,而该过程并非真正被动。此外,这种方法无法检测到仍无法发现的设备。低成本的开源蓝牙开发平台Ubertooth One可以以一种真正的被动方式帮助克服这一限制,使其成为一种有吸引力的数字取证工具。使用基于车辆的传感器和并行多方法设备发现,我们对Ubertooth One进行了被动发现的实用评估,并将其发现率与标准方法进行了对比。基于83个比较现场实验,我们证明Ubertooth One可以产生法医声音观察结果,同时最多可以发现十倍的设备。我们还展示了这种方法可以识别重复设备的存在,因为我们在单个和多个位置方案中的不同日期观察到了2370个重复观察的实例。我们得出的结论是,这种被动技术可以补充标准方法,并且有可能被用作可行的替代方法。

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